Shopify is the commerce platform that powers millions of merchants worldwide. Behind the product experience are ML systems that drive recommendations, search, and personalization at massive scale.

We build the compute and serving layer behind these systems: multi-node GPU training clusters, real-time inference with strict latency budgets, and the performance engineering that keeps it all efficient at scale. Our models serve hundreds of millions of buyers, and the infrastructure we build directly impacts how merchants grow their businesses.

The Role

You will own the core infrastructure that ML ML Engineers depend on to train and serve models: GPU training clusters, real-time serving systems, and the performance and reliability layer underneath both. You'll sit between ML Engineers who need fast iteration and production systems that need to stay up during events like Black Friday/Cyber Monday, where traffic and stakes peak simultaneously.

This role carries real technical authority. You'll make architectural decisions about how we scale training and serving, set standards for infrastructure quality, and be the person the team relies on when systems need to scale by an order of magnitude. You'll mentor engineers across the team, drive alignment on infrastructure direction across multiple workstreams, and influence technical strategy beyond your immediate team. You'll also raise the engineering bar through hiring and technical reviews.

What You'll Do

Training Infrastructure

• Design and operate GPU training pipelines on Kubernetes, including multi-node distributed training on GPU clusters
• Own training reliability: checkpointing, fault tolerance, preemption recovery, and resource scheduling
• Optimize training performance: mixed precision, kernel tuning, data loading throughput, and cluster utilization. You own compute efficiency; data correctness and freshness are owned by the operations side of the team.
• Build abstractions that let ML Engineers launch and iterate on training runs with minimal friction

Serving Infrastructure

• Build and maintain model serving infrastructure for real-time recommendation and LLM inference, with strict latency and throughput requirements
• Optimize serving cost and performance: batching strategies, model compilation, GPU right-sizing, and autoscaling
• Ensure serving systems meet availability and latency targets under peak traffic

Platform & Developer Experience

• Build internal tools and platforms that accelerate the model development lifecycle
• Define infrastructure patterns and best practices adopted across the team
• Improve the inner loop for ML Engineers: faster iteration from code change to training result to production evaluation

Technical Leadership

• Drive cross-team technical strategy for ML infrastructure - identify the next set of problems before they become blockers
• Mentor and up-level engineers on the team through pairing, design reviews, and setting technical standards
• Contribute to hiring: screen candidates, conduct technical interviews, and calibrate the engineering bar
• Write technical proposals and RFCs that shape infrastructure direction across the organization

What We're Looking For

Required

• 7+ years in software engineering, with 5+ years focused on ML infrastructure or distributed systems
• Deep hands-on experience with GPU training at scale: distributed training, checkpointing, fault recovery, and performance tuning. You've debugged real problems like NCCL hangs, gradient synchronization issues, or data loading bottlenecks.
• Strong Kubernetes skills: pod specs, GPU scheduling, resource quotas, debugging scheduling failures, and operating stateful GPU workloads
• Production model serving experience: you've built or operated serving systems behind real user traffic with latency constraints
• Solid Python and systems fundamentals; comfortable reading and modifying PyTorch training code
• Experience designing infrastructure abstractions used by other engineers
• Demonstrated technical leadership: you've driven architecture decisions, written technical proposals, and influenced engineering direction beyond your immediate team
• Track record of mentoring engineers and raising the technical bar on a team

Preferred

• Experience with cloud-native ML orchestration (SkyPilot, Ray, or similar)
• Hands-on with LLM serving stacks (vLLM, TensorRT-LLM, Triton, or equivalent)
• Experience with model compression in production (quantization, pruning, distillation)
• Experience operating recommendation or retrieval systems at scale
• Track record of building internal platforms adopted by other teams

How We Work

• You'll pair directly with ML ML Engineers. Understanding their models well enough to build the right infrastructure abstractions is part of the job.
• We prefer automation over runbooks. If a process can be scripted, it should be.
• On-call is shared. When you're on rotation, your scope is GPU cluster health, training failures, and serving availability - you own it end to end.
• You'll profile GPU kernels, chase p99 latency regressions, and care about FLOPS utilization. This is a deeply technical infrastructure role.
• Research and production are the same codebase. You'll see your infrastructure decisions reflected in real model quality and real merchant outcomes.
• Shopify operates on high trust and low process. You'll have real ownership and the autonomy to make decisions, not just execute tickets.

What Success Looks Like

• In 3 months: You've onboarded to training and serving infrastructure, shipped at least one meaningful improvement to reliability or performance, and can independently debug issues across the GPU stack.
• In 6 months: You own a major infrastructure subsystem (training cluster or serving platform). Researchers are training faster or serving more reliably because of changes you've made.
• In 12 months: You've shaped the technical roadmap for ML infrastructure and influenced engineering direction beyond the team. Other engineers across the organization come to you for architectural guidance. The platform scales to the next generation of models because of the systems and standards you've put in place. You've made the team stronger through hiring and mentorship.

Shopify is the commerce platform that powers millions of merchants worldwide. Behind the product experience are ML systems that drive recommendations, search, and personalization at massive scale.

We build and maintain the operational backbone behind these systems: deployment pipelines, evaluation frameworks, data preprocessing, and the monitoring that keeps models fresh and reliable in production. Our models serve hundreds of millions of buyers, and the pipelines we build directly impact how quickly and safely we can improve merchant outcomes.

The Role

You will own the operational lifecycle of our ML systems: deployment pipelines, evaluation frameworks, data pipelines, and the monitoring and reliability layer that keeps everything running in production. You'll ensure models go from training to production safely, that we can evaluate changes rigorously, and that the data feeding our models is fresh and correct.

This role is the connective tissue between research and production. You'll build the systems that let engineers ship model improvements with confidence and speed, while maintaining the reliability standards required to serve hundreds of millions of buyers - including during peak events like Black Friday/Cyber Monday.

This role carries real technical authority. You'll set the standards for how models get deployed and evaluated, mentor engineers on operational best practices, and drive alignment on reliability and pipeline strategy across the team. You'll influence technical direction beyond your immediate team and raise the engineering bar through hiring and technical reviews.

What You'll Do

Deployment & Rollout

• Own the model deployment pipeline end to end: export, validation, canary rollout, rollback, and A/B integration
• Build and maintain CI/CD for ML: automated testing, model validation gates, and progressive delivery
• Ensure safe, repeatable deployments with clear rollback paths and minimal manual intervention

Evaluation & Experimentation

• Build automated offline evaluation pipelines against production baselines
• Extend our experimentation framework so ML Engineers can launch and evaluate model changes with minimal friction
• Maintain evaluation datasets and ensure data freshness and correctness
• Integrate offline metrics with online A/B testing to close the feedback loop

Data Pipelines

• Own data preprocessing for training: interaction histories, feature stores, and embedding tables
• Manage workflow orchestration (Airflow or equivalent) for scheduled retraining and data refresh. You trigger and monitor training runs; the underlying GPU compute layer is owned by the infrastructure side of the team.
• Ensure data quality, lineage tracking, and pipeline idempotency
• Own data correctness and freshness; partner with infrastructure engineers on data loading throughput and efficiency

Monitoring & Reliability

• Build monitoring and alerting across training jobs, serving endpoints, and data pipelines
• Define and maintain SLOs for model freshness, serving latency, and training throughput
• Participate in incident response and drive post-mortems for ML system failures
• Identify and eliminate toil through automation

Technical Leadership

• Drive cross-team technical strategy for ML operations - identify systemic reliability risks and pipeline bottlenecks before they become incidents
• Mentor and up-level engineers on the team through pairing, design reviews, and setting operational standards
• Contribute to hiring: screen candidates, conduct technical interviews, and calibrate the engineering bar
• Write technical proposals and RFCs that shape operational direction across the organization

What We're Looking For

Required

• 7+ years in software engineering, with 5+ years focused on MLOps, data engineering, or production ML systems
• Strong experience with ML deployment pipelines: model export, validation, canary releases, and rollback strategies
• Experience with workflow orchestration for ML (Airflow, Dagster, Prefect, or similar)
• Solid Python fundamentals; comfortable working with PyTorch model artifacts and training configurations
• Production monitoring experience: you've built or operated alerting, dashboards, and SLO frameworks for ML systems
• Experience with data pipelines at scale: batch processing, feature engineering, and data quality validation
• Working proficiency with Kubernetes: able to debug pod failures, understand resource scheduling, and navigate GPU workloads
• Demonstrated technical leadership: you've driven operational strategy, written technical proposals, and influenced engineering direction beyond your immediate team
• Track record of mentoring engineers and raising the reliability bar on a team

Preferred

• Experience with large-scale data warehouses (BigQuery or equivalent) for offline evaluation and metrics
• Hands-on with experiment tracking and A/B testing frameworks
• Experience operating recommendation or retrieval systems at scale
• Familiarity with model compression workflows in production (quantization, pruning, distillation)
• Experience with cloud-native ML orchestration (SkyPilot, Ray, or similar)

How We Work

• You'll pair directly with ML Engineers. Understanding their models well enough to build the right operational workflows is part of the job.
• We prefer automation over runbooks. If a process can be scripted, it should be.
• On-call is shared. When you're on rotation, your scope is pipeline failures, data freshness alerts, deployment rollbacks, and evaluation integrity - you own it end to end.
• You'll dig into Airflow DAG failures, data drift alerts, and deployment validation issues. This is a deeply operational role with high production stakes.
• Research and production are the same codebase. You'll see your operational decisions reflected in real model quality and real merchant outcomes.
• Shopify operates on high trust and low process. You'll have real ownership and the autonomy to make decisions, not just execute tickets.

What Success Looks Like

• In 3 months: You've onboarded to deployment and evaluation pipelines, shipped at least one meaningful improvement to deployment safety or developer experience, and can independently debug issues across the operational stack.
• In 6 months: You own a major subsystem (deployment pipeline, evaluation framework, or data pipelines). Researchers are shipping model changes faster or more safely because of improvements you've made.
• In 12 months: You've shaped the operational roadmap for ML systems and influenced engineering direction beyond the team. Deployments are faster and safer, evaluation is more rigorous, and the team trusts the pipelines you've built. Other engineers across the organization come to you for guidance on ML operational best practices. You've made the team stronger through hiring and mentorship.

Step into the engine room of Agentic Commerce! Imagine owning the bleeding edge of machine learning at Shopify, where your acceleration, optimization, and scaling of ML inference will shape the experience of millions of merchants, and influence how commerce AI is done worldwide. We’re seeking a Senior Staff Engineer to architect, optimize, and own the high-performance runtime that transforms innovative models into production breakthroughs. Your work will be the engine behind our real-time AI systems, driving game-changing cost and latency reductions, and enabling rapid launches of intelligent features that keep Shopify (and our merchants) years ahead. Join a remote-first team of world-class experts, experiment fearlessly, and see your code move the needle for some of the largest-scale ML workloads in commerce.

Responsibilities

• Architect, optimize, and own Shopify’s production ML inference. Designing for high throughput, ultra-low latency, and global reliability.
• Leverage and extend technologies like CUDA, TensorRT, Triton, TVM, and custom GPU kernels to deliver state-of-the-art performance and efficiency at scale.
• Partner with ML, infrastructure, and product teams to seamlessly deploy, benchmark, and scale cutting-edge models powering our platform.
• Drive cost optimization and system efficiency, reducing cloud spend and carbon footprint by orders of magnitude without sacrificing model quality.
• Lead deep performance investigations, apply advanced techniques (pruning, quantization, distillation, batching), and implement robust solutions for serving models in production.
• Set technical strategy and culture for ML inference across Shopify, mentoring others and collaborating with global AI pioneers.

Qualifications

• Proven, hands-on expertise in building and optimizing large-scale ML inference systems, with measurable performance and cost wins.
• Deep experience in production model serving, runtime optimization, and acceleration. Especially leveraging GPUs (CUDA, TensorRT) and high-performance deep learning infrastructure.
• Strong software engineering skills (Python, C++, and/or other relevant languages) with a robust systems and distributed computing mindset.
• Demonstrated leadership in architecting or scaling reliable, real-time inference at scale, handling millions of queries per day.
• Track record of cross-functional impact: working closely with ML research/engineering, infra, and product teams to deliver production results.
• Advanced understanding of model compression, quantization, efficient deployment, and tradeoffs between speed, cost, and accuracy.

Nice to Haves

• Open source contributions to inference frameworks (TensorRT, TVM, Triton, DeepSpeed, ONNX, etc.) or technical talks/publications at leading AI conferences.
• Experience optimizing inference across a variety of hardware (NVIDIA, AMD, ARM, cloud TPUs).
• Familiarity with building or integrating robust monitoring, observability, and auto-scaling for inference platforms.
• Experience with modern MLOps pipelines and methodologies.
• Prior experience in e-commerce, large-scale product infra, or globally distributed inference workloads.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.

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Data Platform Engineers

• Remote - Americas
• Engineering & Data

Apply Now

About the role

Data Platform Engineers build and support the infrastructure that enables our Data Engineers and Scientists to thrive. At every stage of the data lifecycle, from ingestion and transformation to data discovery and reporting, we build infrastructure and tools that are on the cutting edge of data.

Why you’ll love building Shopify’s data platform:

• We’ve got a whole lot of data. Every problem we work on has to consider scale from the start.
• We stand on firm foundations. We solve the high rung problems that take mature infrastructure for granted - our data platform is built on top of mature offerings from Google Cloud Platform. We’re especially interested in candidates who have experience working with GCP services.
• We focus on incremental progress and impact. Even though we build big, we ship incrementally. Your work won’t sit months waiting to get in the hands of our users.
• There’s lots of opportunity for that impact. We’ve spent the last year migrating away from a nearly decade old legacy system. We’ve tackled the core use cases and now we’re at an inflection point, with a solid foundation and clear places where we can make life better for our users.

Ready to build the backbone of Shopify? Join the team that's making commerce better for everyone.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.

This role may require on-call work

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

Apply Now

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I'm still learning the ropes, so I focus more on learning myself, rather than mentoring others.I'm comfortable with my skills, but I haven’t done any official mentoring.I actively mentor less experienced engineers, sharing my knowledge and often lead team discussions.I am a craft mentor across the organisation, and am often consulted on high-level decisions.

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Welcome to Shopify's engine room of innovation. As an Applied Machine Learning Engineering Manager, you will lead teams in crafting groundbreaking ML solutions that redefine connections between millions of merchants and buyers. Your role is to guide ML engineers in making strategic decisions that advance LLMs, agents, and address large-scale real world problems. With a focus on developing extensive models, enhancing search, refining recommendations, and personalizing experiences, your leadership will transform what's currently considered possible in the space of AI-driven commerce.

Key Responsibilities:

• Lead teams to design, refine, and deploy ML models that revolutionize commerce solutions.
• Spearhead initiatives integrating LLMs, agents, and multimodal models into Shopify’s ecosystem.
• Apply machine learning techniques to real world problems by enhancing optimized search and personalized recommendations.
• Cultivate a collaborative culture emphasizing technical excellence, learning, and innovation.

Qualifications:

• Extensive experience managing teams to implement large-scale ML models.
• Proficiency in TensorFlow or PyTorch, and strong Python skills.
• Proven problem-solving skills in complex, real-world product environments.
• Excellent communication skills with a track record of thriving in dynamic settings.

Ready to lead on the bleeding edge of AI? Join the team that's making commerce better for everyone.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, coming prepared with your own IDE.

This role may require on-call work.

Machine Learning Infrastructure Engineers build and operate the end-to-end platform that powers AI—from data ingestion and training to large-scale, low-latency inference. They design high-performance, GPU-accelerated systems on Kubernetes, craft self-serve developer experiences, and ship the paved roads that let ML teams move fast, safely, and at global scale. Some companies separate ML Infra, ML Platform and ML Ops- at Shopify- we call this ML Infrastructure. We have an agile workforce who can flex their experience and solve problems across these three domains.

Responsibilities:

• Build and operate ML control planes, APIs, CLIs, SDKs, and self-serve golden paths
• Design and optimize multi-tenant GPU Kubernetes clusters, including autoscaling, scheduling, packing, and utilization
• Own model lifecycle: training orchestration/experiments, registries/versioning, CI/CD, canary/blue-green, and safe rollback
• Build real-time serving stacks (KServe/Seldon/TensorFlow Serving) and end-to-end pipelines for batch and streaming
• Design feature platforms and engineer storage/data movement for datasets, features, and artifacts tuned for cost/performance
• Implement observability and SLOs across pipelines, training, and inference; automate remediation and capacity planning
• Partner with ML, data, and product teams to unblock delivery and accelerate idea-to-impact

Qualifications:

• Proven platform/infrastructure engineering experience with a track record of shipping production systems and code
• Deep Kubernetes/containerization expertise for ML workloads (operators, Helm, service mesh/gRPC) and multi-tenant clusters
• Hands-on experience running GPU infrastructure at scale (NVIDIA ecosystem; scheduling/packing/optimization)
• Strong distributed systems and API/service design fundamentals; experience with high-scale inference
• Proficiency with infrastructure-as-code and automation (Terraform, Helm, GitOps) on major clouds (GCP/AWS/Azure)
• Observability expertise (Prometheus/Grafana) and SLO-driven operations for ML systems
• Proficient in Python/Go/Java; experience building developer tooling and self-service platforms

Nice to Haves:

• Model serving and lifecycle tooling: KServe/Seldon/TensorFlow Serving, Kubeflow, MLflow/W&B, model registries, DVC
• Feature store experience (Feast/Tecton) with online/offline parity and SLAs
• Data infrastructure familiarity (Kafka, Spark/Flink) and stateful stores (Redis/MySQL); CI/CD for online/batch inference
• Model performance optimization (batching, caching, quantization, distillation) and hardware-aware tuning
• Experience with experimentation/A/B testing platforms and online evaluation frameworks

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.

This role may require on-call work

We're building the future of Real-Time Merchant Analytics at Shopify!

As a Staff Engineer you'll be at the forefront of reimagining how merchant data flows through modern streaming architectures. This isn't your typical infrastructure role – you'll be crafting solutions that challenge conventional approaches to data processing at global scale.

What Makes This Exciting?

You'll work across multiple languages and technologies – Java, Ruby, Python, SQL, Flink, and ClickHouse – choosing the right tool for each challenge, model data elegantly, and turning data pipeline development into a configuration exercise rather than a coding marathon.

You'll tackle fascinating problems: How do you architect lightning-fast real-time modeling that seamlessly combines data from multiple tables? How do you handle late-arriving data in distributed streams? What's the most elegant approach to backfill terabytes while maintaining real-time processing?

We embrace AI and LLMs to accelerate repetitive tasks, freeing you to focus on the creative problem-solving that makes this work truly rewarding.

If you love turning "impossible" requirements into beautiful solutions, this is your playground.

What You'll Do

• Architect, build, and refine high-performance streaming infrastructure tailored to large-scale, real-time merchant analytics.
• Develop tools and frameworks to boost platform efficiency, scalability, and developer experience across the team.
• Collaborate with cross-functional teams to integrate streaming systems with Shopify's broader data ecosystem.
• Partner with product and data teams to influence the technical roadmap and shape the future of merchant analytics.
• Mentor and uplevel engineers on the team, fostering an environment of innovation and technical excellence.

What You'll Need

• Extensive experience in data infrastructure engineering, particularly in building and scaling real-time data platforms.
• Strong knowledge of Apache Flink or similar stream processing frameworks (Kafka Streams, Spark Streaming).
• Proficiency in multiple programming languages (Java, SQL required; Python, Ruby a plus).
• Experience with analytical databases like ClickHouse or BigQuery.
• Strong understanding of containerization (Docker, Kubernetes).
• Deep expertise in handling distributed systems challenges: late-arriving data, exactly-once semantics, backfill strategies, and data consistency.
• Outstanding problem-solving skills with a focus on complex technical challenges at scale.
• A collaborative mindset and the ability to thrive in a diverse, dynamic team environment.

Great advertising connects merchants with customers who genuinely need what they're selling. As a Machine Learning Engineer focused on Ads, you'll build the targeting and personalization technology that makes these meaningful connections happen at scale. You'll develop sophisticated machine learning models that help merchants reach the right audience at exactly the right moment, creating advertising experiences that drive real business growth while respecting the customer experience.

Key Responsibilities:

• Develop and optimize advanced machine learning models for ad targeting and personalization systems
• Analyze comprehensive ad performance data to identify optimization opportunities and maximize ad spend efficiency
• Collaborate closely with advertising teams to integrate ML solutions seamlessly into our ad platform
• Research and implement innovative algorithms and tools to enhance ad relevance and effectiveness
• Document technical insights and share best practices across engineering teams

Qualifications:

• Extensive experience building and deploying machine learning models for advertising systems at scale
• Strong proficiency in ML frameworks including TensorFlow or PyTorch, with expert-level Python programming skills
• Proven analytical skills for processing and extracting insights from large-scale datasets
• Demonstrated problem-solving abilities and innovative thinking in ad technology solutions
• Solid familiarity with ad platforms, A/B testing methodologies, and data-driven decision making processes
• Experience with statistical methods and performance optimization for ML systems

Ready to connect merchants with their perfect customers? Join the team that's making commerce better for everyone.

*At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.

This role may require on-call work*

The role's core focus is on building and managing Shopify's compliance programs for our advanced IT systems, it offers a unique opportunity to work in a flexible compliance environment where expertise, innovation, and unconventional approaches are highly valued.

In this role, you have the autonomy to discover, analyse, and solve security and compliance problems at scale. Resourcefulness is key - you’ll need to be able to quickly gather context on infrastructure, systems, software, and safeguards to help Shopify continue shipping and scaling while staying secure, trustworthy, and usable.

A ‘day in the life’ of this role may include any, or all, of the following:

• Writing and updating code that automates and supports audit and compliance programs.
• Meeting with SMEs from Production Engineering, Security Engineering, Product, Legal, and other areas to learn how Shopify works and ensure that the compliance programs accurately reflect what we do and how we do it.
• Engaging with external auditors to design and perform audits for programs such as SOC, SOX, PCI and others.
• Providing expert advice to Shopify teams with regard to security and compliance domains you manage

We want a dynamic technical expert capable of managing projects, solving complex problems, simplifying solutions, and inspiring and up-skilling the team.

This role is ideal for you if you are someone who enjoys being hands-on and building technical things to support your work. You must also be able to organize others as you build and manage complex security compliance programs for a fast paced engineering focused environment.

Qualifications:

• Proven experience performing assurance and advisory roles relating to Information Technology with particular emphasis on system implementations, technical security configurations, and cloud native environments
• Hands-on experience building data analytics, reporting solutions and task automation tooling
• Experience evaluating IT, security and application controls in the context of a compliance program for a company of similar size and complexity of Shopify
• Strong knowledge of industry risk and compliance frameworks such as NIST, ISO, SOX, SOC, and PCI-DSS
• Excellent analytical and problem-solving skills, with the ability to think strategically and identify innovative solutions to complex challenges
• Strong project management skills, with the ability to prioritize and manage multiple initiatives simultaneously using agile project management methodologies
• Exceptional communication and interpersonal skills, with the ability to effectively collaborate with stakeholders
• Self-motivated and adaptable, with a strong drive for continuous learning and professional growth

Responsibilities:

• Be a security expert responsible for owning and building compliance activities for standards such as: SOC, PCI, SOX and others
• Dive deep into new products or initiatives to surface and analyse the impact on security compliance engineering
• Leverage data and visualization tools to identify areas for improvement, track progress and inform trusted decisions
• Be a strong and credible influencer among cross functional engineering and business teams
• Actively seek out opportunities to develop and deploy automations that will increase team efficiency
• Anticipate changes in our trust and security posture as the technical footprint and company operations change, and help propose solutions to adapt to change
• Develop safeguards, systems and policies that meet compliance requirements while balancing the need to move fast and stay innovative

Step into the future of AI with Shopify, where you'll be at the helm of cutting-edge machine learning innovation that transforms commerce and solves complex challenges. Leverage your expertise in Natural Language Processing (NLP), Large Language Models (LLMs), and AI solutions to design, develop, and deploy state-of-the-art machine learning models. Work on impactful projects that enhance our products and services, ensuring AI solutions are effective, ethical, and scalable.

Key Responsibilities:

• Design and implement machine learning models in NLP and LLMs to address business challenges and improve customer experiences.
• Collaborate with cross-functional teams to integrate AI solutions into products for seamless deployment.
• Conduct research and experimentation to explore new methodologies and technologies, staying at the forefront of advancements in AI.
• Optimize models for production environments, focusing on scalability, efficiency, and performance.
• Analyze complex datasets to derive actionable insights for product development and strategy.
• Contribute to the academic community through publications and patents, sharing innovations with the broader field.

Qualifications:

• Proven experience in developing and deploying machine learning models, particularly in NLP and LLMs (e.g., BERT, T5, GPT).
• Proficiency in programming languages such as Python, with experience in ML frameworks (e.g., TensorFlow, PyTorch).
• Strong understanding of AI, model optimization, and deployment strategies.
• Excellent analytical skills with the ability to communicate complex ideas effectively.
• Ph.D. or Master’s degree in Computer Science, Data Science, or a related field with a focus on machine learning and AI is preferred but not required.

*At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.

This role may require on-call work. Ready to redefine the future of AI with innovative solutions? Join the team that’s making commerce better for everyone.*

Join Shopify's innovative team as we work on the development and implementation of state of the art HSTU models (Hierarchical Sequential Transduction Unit) to recommend the best growth drivers and action for merchants and buyers. You'll play a pivotal role in solving high-impact data problems that directly improve merchant success and consumer experience.

As a Machine Learning Engineering (MLE) lead or individual contributor, you'll be at the forefront of building AI solutions that anticipate both merchant needs and personalization for 100M+ shoppers.

Key Responsibilities:

• Develop and deploy Generative AI, natural language processing, and HSTU-based recommendation models at scale
• Design and implement scalable AI/ML system architectures supporting models
• Build sophisticated inference pipelines that process billions of events and deliver real-time recommendations
• Implement data pipelines for model training, fine-tuning, and evaluation across diverse data sources (merchant events, consumer interactions, payment sequences)
• Experiment with novel architectures
• Optimize for production through advanced techniques like negative sampling, ANN search, and distributed GPU training
• Collaborate cross-functionally with product teams, data scientists, and infrastructure engineers to deliver measurable business impact
• Communicate effectively with both technical and non-technical audiences, translating complex ML concepts into actionable insights

Qualifications:

• Mastery in recommendation systems, Gen AI or LLMs
• End-to-end experience in training, evaluating, testing, and deploying machine learning products at scale.
• Experience in building data pipelines and driving ETL design decisions using disparate data sources.
• Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent, and orchestration tools.
• Experience with running machine learning in parallel environments (e.g., distributed clusters, GPU optimization).
• This role may require on-call work.

*At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.

This role may require on-call work.*Ready to redefine e-commerce through AI innovation? Join the team that’s making commerce better for everyone.

Every day, millions of people search for products across Shopify's ecosystem. That's not just queries—that's dreams, businesses, and livelihoods riding on whether someone finds the perfect vintage jacket or the exact drill bit they need. As a Machine Learning Engineer specializing in Search Recommendations, you'll be the one making that magic happen. With a search index unifying over a billion products, you're tackling one of the hardest search problems at unprecedented scale. We're building cutting-edge product search from the ground up using the latest LLM advances and vector matching technologies to create search experiences that truly understand what people are looking for.

Key Responsibilities:

• Design and implement AI-powered features to enhance search recommendations and personalization
• Collaborate with data scientists and engineers to productionize data products through rigorous experimentation and metrics analysis
• Build and maintain robust, scalable data pipelines for search and recommendation systems
• Develop comprehensive tools for evaluation and relevance engineering, following high-quality software engineering practices
• Mentor engineers and data scientists while fostering a culture of innovation and technical excellence

Qualifications:

• Expertise in relevance engineering and recommendation systems, with hands-on experience in Elasticsearch, Solr, or vector databases
• Strong proficiency in Python with solid object-oriented programming skills
• Proven ability to write optimized, low-latency code for high-performance systems
• Experience deploying machine learning, NLP, or generative AI products at scale (strong plus)
• Familiarity with statistical methods and exposure to Ruby, Rails, or Rust (advantageous)
• Track record of shipping ML solutions that real users depend on

Ready to make search more magical? Join the team that's making commerce better for everyone.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.
This role may require on-call work

At Shopify, our Applied Machine Learning Engineers tackle the most challenging technical problems in commerce. By leveraging vast datasets and cutting-edge machine learning technologies, like multimodal LLMs, embeddings, etc., you will develop ways that redefine how merchants connect with buyers. Your work will empower merchants with advanced tools and systems that enhance search, discovery, and agents at a global scale.

As an Applied Machine Learning Engineer, you will work with petabyte-scale data and utilize state-of-the-art ML methods to build and deploy models that serve millions of users. You'll be at the forefront of AI innovation, using technologies including LLM posttraining, reinforcement learning, and model quantization, to redefine what’s possible in e-commerce.

Key Responsibilities:

• Analyze and interpret large-scale datasets to drive model development and optimization.
• Collaborate with cross-functional teams to integrate ML solutions into Shopify's core products.
• Design, build, and deploy agents and multimodal LLMs that improve merchant and buyer interactions.
• Stay current with the latest advancements in machine learning technologies and frameworks.
• Document and share technical insights and best practices across teams.

Qualifications:

• Extensive experience in building and deploying machine learning models at scale.
• Proficiency in using ML framework (e.g., TensorFlow, PyTorch) and programming languages like Python.
• Strong analytical and problem-solving skills in solving real-world product problems.
• Excellent communication skills and the ability to work in a fast-paced, collaborative environment.

Ready to deploy your next breakthrough model? Join the team that’s making commerce better for everyone.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.

This role may require on-call work

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Applied ML Engineering - GenAI, AI Agent

• Remote - Americas
• Engineering & Data

Apply Now

About the role

Join Shopify's innovative team as we develop an AI Personal Shopper to transform the online shopping experience. Leveraging cutting-edge AI, including Large Language Models (LLM) and advanced machine learning algorithms, you'll play a pivotal role in delivering personalized recommendations and insightful suggestions tailored to individual preferences. Our goal is to redefine e-commerce by creating a concierge service that enhances how customers interact with Shop and Storefronts. As a Machine Learning Engineering (MLE) lead or individual contributor, you'll be at the forefront of implementing AI systems at scale, directly empowering merchants and creating tangible solutions with real-world impact.

Key Responsibilities:

• Develop and deploy Generative AI, natural language processing, and machine learning models.
• Design and produce scalable AI/ML system architectures.
• Implement data pipelines for fine-tuning LLMs.
• Solve high-impact data problems, delivering business impact through data and machine learning products.
• Prioritize and communicate effectively with both technical and non-technical audiences.

Qualifications:

• Mastery in building data products using generative AI, RLHF, and fine-tuning LLMs.
• End-to-end experience in training, evaluating, testing, and deploying machine learning products at scale.
• Experience in building data pipelines and driving ETL design decisions using disparate data sources.
• Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent, and orchestration tools.
• Experience with running machine learning in parallel environments (e.g., distributed clusters, GPU optimization).

*At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.

This role may require on-call work. Ready to redefine e-commerce through AI innovation? Join the team that’s making commerce better for everyone.*

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

Apply Now

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Name*

Email*

Location*

Start typing and select a location from the dropdown.

Resume*

Linkedin Profile

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If you've contributed to the largest open-source projects, optimized systems to handle unprecedented traffic, or developed game-changing algorithms, we want to know about it. Link your highlights and skip the resume.

Message to hiring manager:

Do you have the right to work in your listed location?*

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

How many years of hands-on ML modeling and development do you have? (Not including academic experience or internships)*

0-2 years3-5 years6-8 years8+ years

How would you describe your comfort with Object Oriented Programming?*

I am still learning but with support can code in OOPI work more efficiently in another type of programmingI am comfortable and confident I would do well in an Object Oriented Pair Programming interviewI am an expert

What parts of the Model Development Lifecycle have you managed?*

Problem definition, data collection and trainingResearch, feature engineering tuning, training, deployment, maintenanceTuning, training, interpretation and production

Give us an example of your work with generative AI.*

Which models are you comfortable using to determine feature importance?*

Linear RegressionDecision treesDeep LearningAll of the above

Please confirm you've read and agree with our candidate NDA*

NDA here

Please confirm you've read our applicant privacy notice*

Privacy notice here

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

Learn more about our Design Apprentice Program

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Great advertising connects merchants with customers who genuinely need what they're selling. As a Staff Software Engineer focused on Ads, you'll build the targeting and personalization technology that makes these meaningful connections happen at scale. You'll develop state of the art ad platform features that help merchants reach the right audience at exactly the right moment, creating advertising experiences that drive real business growth while respecting the customer experience.

Key Responsibilities:

• Design and optimize real‑time ad serving, auction, and ranking systems with p99 latency targets.
• Solve complex ad performance problems to identify optimization opportunities that impact millions
• Collaborate closely with advertising data teams to integrate data driven solutions seamlessly into our ad platform
• Ship experimentation tooling for ad A/B testing
• Document technical insights and share best practices across engineering teams
• Participate in on-call work to ensure reliability and performance of Shopify’s ad systems.

Qualifications:

• Strong Engineering proficiency and a passion for exploring the limits of technology
• Strong with streaming and low‑latency systems: Kafka, Flink/Spark Streaming; feature stores; high‑QPS caches/KV stores (Redis/Aerospike/RocksDB)
• Experience in building scalable, ad-centric applications that enhance the commerce experience
• Demonstrated problem-solving abilities and innovative thinking in ad technology solutions
• Excellent communication skills to convey technical ideas effectively
• A growth-oriented mindset, constantly seeking to improve and innovate.

Nice to have:

• Fluency in ads metrics and levers: CTR, CVR, CPC/CPM/CPA, eCPM, ROAS, LTV, win rate, fill rate, pacing accuracy—and how to move them.

*At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.

This role may require on-call work*

Ready to connect merchants with their perfect customers? Join the team that's making commerce better for everyone.

Are you ready to decode commerce through the power of data? As a Senior Data Scientist at Shopify, you'll work with one of the world's richest commerce datasets - millions of merchants generating billions of transactions across the entire buying journey. You'll deeply understand our products, tell their stories, and figure out how to make them 10x better.

This is data science at unprecedented scale. Every analysis you run, every model you build directly impacts how millions of entrepreneurs grow their businesses and how billions of people shop worldwide. You'll own big problems and collaborate with cross-functional partners to build data-informed solutions that transform commerce from first click to final delivery. As the architect of insights that guide our product journey, you'll determine what we build and how we build it - all while moving at the velocity that makes Shopify legendary.

We're hiring across multiple levels and teams, each offering unique challenges and opportunities: Checkout, Search, Shop, Merchant Services, Infrastructure Data, Revenue Data, Executive Insights, and more. Every team applies different methodologies to solve distinct problems - from real-time ML to causal inference - ensuring you'll grow your skills while shaping how commerce works globally.

Key Responsibilities

• Unearth insights through advanced analytics and data exploration across billions of transactions to inform product strategy and development
• Partner with product managers and engineers to translate complex datasets into actionable strategies
• Apply statistical models, regression analysis, segmentation techniques, and experimental methods to optimize product performance at massive scale
• Build powerful data products that improve the experience of millions of merchants worldwide - from product discovery through post-purchase
• Influence decision-making by providing clear, data-backed recommendations that shape how commerce evolves
• Continuously innovate by leveraging cutting-edge analytics techniques, including AI/ML tools where applicable

Qualifications

• Strong mastery of SQL
• Proficiency in programming languages such as Python, and experience with data visualization tools
• Proven experience in statistical analysis, data modelling, and machine learning at scale
• Skilled in translating complex data into actionable insights that drive business outcomes
• Ability to own and solve complex product and business problems with data in ambiguous, fast-moving environments
• Demonstrated ability to thrive working at startup speed with enterprise impact
• Track record of shipping data products that create value

Ready to transform data into groundbreaking commerce solutions? Join the team that's making commerce better for everyone.

Are you ready to decode commerce through the power of data? As a Staff Data Scientist at Shopify, you'll work with one of the world's richest commerce datasets - millions of merchants generating billions of transactions across the entire buying journey. You'll deeply understand our products, tell their stories, and figure out how to make them 10x better.

This is data science at unprecedented scale. Every analysis you run, every model you build directly impacts how millions of entrepreneurs grow their businesses and how billions of people shop worldwide. You'll own big problems and collaborate with cross-functional partners to build data-informed solutions that transform commerce from first click to final delivery. As the architect of insights that guide our product journey, you'll determine what we build and how we build it - all while moving at the velocity that makes Shopify legendary.

We're hiring across multiple levels and teams, each offering unique challenges and opportunities: Checkout, Search, Shop, Merchant Services, Infrastructure Data, Revenue Data, Executive Insights, and more. Every team applies different methodologies to solve distinct problems - from real-time ML to causal inference - ensuring you'll grow your skills while shaping how commerce works globally.

Key Responsibilities

• Unearth insights through advanced analytics and data exploration across billions of transactions to inform product strategy and development
• Partner with product managers and engineers to translate complex datasets into actionable strategies
• Apply statistical models, regression analysis, segmentation techniques, and experimental methods to optimize product performance at massive scale
• Build powerful data products that improve the experience of millions of merchants worldwide - from product discovery through post-purchase
• Influence decision-making by providing clear, data-backed recommendations that shape how commerce evolves
• Lead high-impact projects through complex, ambiguous problems while mentoring others
• Continuously innovate by leveraging cutting-edge analytics techniques, including AI/ML tools where applicable

Qualifications

• Strong mastery of SQL
• Proficiency in programming languages such as Python, and experience with data visualization tools
• Proven experience in statistical analysis, data modelling, and machine learning at scale
• Skilled in translating complex data into actionable insights that drive business outcomes
• Ability to own and solve complex product and business problems with data in ambiguous, fast-moving environments
• Demonstrated ability to thrive working at startup speed with enterprise impact
• Track record of shipping data products that create value

Ready to transform data into groundbreaking commerce solutions? Join the team that's making commerce better for everyone.

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Staff Security Engineer

• Remote - Americas
• Engineering & Data

Apply Now

About the role

We are hiring staff security engineers who build impactful solutions fast. You will protect our company, our merchants and our data against any and all cyber risks. You will help Shopify maintain a high-trust operating environment by building tailored detection and response solutions.

Key Responsibilities

• Design, build and ship security solutions that defend against cyber attacks and data exfiltration
• Champion cross-functional projects
• Respond to and lead incident response for critical security events
• Cut through complexity to focus on high-impact work that reduces real risk
• Partner with IT, legal, and business teams to mitigate threats and remediate for the long-term
• Communicate security risks and technical recommendations to both technical and non-technical stakeholders

Qualifications

• Expertise in building great software in the security detection and response domain
• Broad expertise in endpoint security, enterprise IT security and cloud security
• Proven experience responding to cyber security incidents
• Active awareness of emerging threats and AI-enabled attack vectors including prompt injection, supply chain compromises and social engineering
• Experience building real AI solutions that deliver tangible value to security operations, not just novel experiments
• Proficiency in Python, Swift and GCP; with Cursor and other AI tools
• Excellent communication skills: you can distill complex security data into clear, actionable insights
• Brings senior-level judgment and operates with high autonomy, proactively identifying and driving work from ambiguity to outcomes

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

Apply Now

Application

*Required

Name*

Email*

Resume*

Linkedin Profile*

Location*

Start typing and select a location from the dropdown.

Do you now or in the future require sponsorship to work in the country of employment?

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

Please confirm you've read and agree with our candidate NDA*

NDA here

Please confirm you've read our applicant privacy notice*

Privacy notice here

Please confirm if you agree to your Shopify interview(s) being recorded and transcribed to help improve our hiring process. Agreeing/not agreeing to recording has no impact on our hiring decision.

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

Learn more about our Design Apprentice Program

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• Privacy Policy

Back

Staff Data Engineers

• Remote - Americas
• Engineering & Data

Apply Now

About the role

Build the data systems that power global commerce. As a Staff Data Engineer at Shopify, you'll architect pipelines that transform complex information into valuable insights. Your work will shape our technical direction and help millions of merchants make smarter decisions. Whether optimizing data models or creating new analytics tools, your expertise drives what's possible here. Ready to solve challenges that matter?

Key Responsibilities:

• Design and implement scalable models and pipelines that drive insights and innovation.
• Transform raw information into intelligence to support merchant success and excellence.
• Collaborate closely with product teams to ensure quality and integrity across platforms.
• Optimize workflows and infrastructure to enhance performance and scalability.
• Lead efforts in peer-reviewing and standardizing practices to uphold benchmarks.

This role may require on-call work.

Qualifications:

• Extensive data modeling experience, utilizing various paradigms and techniques.
• Strong analytical skills and experience with visualization tools.
• Proficiency with SQL, Python, and relevant technologies.
• Experience with batch transformation and warehouse layers on cloud platforms such as AWS, GCP, or Azure.
• Proven ability to translate complex information into strategic insights while working effectively with teams.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days.

Ready to turn raw data into product gold? Join the team that’s making commerce better for everyone.

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

Apply Now

Application

*Required

Name*

Email*

Location*

Start typing and select a location from the dropdown.

Resume

Linkedin Profile

Alternative Link

If you've contributed to the largest open-source projects, optimized systems to handle unprecedented traffic, or developed game-changing algorithms, we want to know about it. Link your highlights and skip the resume.

Message to hiring manager:

Do you have the right to work in your listed location?

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

How many years of professional experience do you have in data engineering, not including academic experience and internships?*

0-3 years3-5 years5-7 years7-10 years10+ years

As a Data Engineer, how would you describe your approach to mentorship?*

I'm still learning the ropes, so I tend to focus more on absorbing knowledge myself.I'm comfortable with my skills, but I still rely on more experienced engineers for complex problems.I mentor others and promote a culture of learning and growth within the organization.I mentor others, and play a role in increasing the technical competencies of my craft at the org level.

As a Data Engineer, how would you describe your experience on projects?*

I haven't led a project yet, but I've contributed to the tasks assigned to me and learned from the process.I've led a small project or a part of a larger project from start to finish.I've led multiple projects across teams and stakeholders, and was accountable for the project's success.I've led high-stakes projects spanning multiple stakeholders, disciplines, and technical complexities.

Describe your experience with data architecture and modeling concepts in your current or previous roles.*

I have contributed to building data models within a data warehouse, with a clear and defined scope.I've contributed to and led data modeling and design within a data warehouse, with an ambiguous scope.I've led data modeling and design for complex concepts within a data warehouse frameworkI regularly lead the design and modeling of complex, large-scale data warehouse systems.

As a Data Engineer, what area would you prioritize for your main focus, aligning with your expertise and interest?*

Bringing data onto or from a data platform (ETL/ELT), managing API interactions, and monitoring pipelines.Building tooling and frameworks crucial for data processing and exposure, and creating custom software.Data modeling, incorporating intricate business logic, and constructing a robust data warehouse.Streaming data pipelines, delivering real-time data transport solutionsData science and analytics, constructing data marts for in-depth data analysis, and serving the business.

What excites you most about joining Shopify and this role?

Please confirm you've read and agree with our candidate NDA*

NDA here

Please confirm you've read our applicant privacy notice*

Privacy notice here

Share an AI-assisted or vibe-coded work sample (optional)

Want to stand out? Optionally share something you’ve made with an AI tool — e.g. a “sell yourself” build, a short project, or a creative take on your background — that shows why we should consider you and how you work with AI. We’re interested in your taste, effort, and the quality of what you produce. Submit a link, paste your code or output, or attach a file. Not required to apply.

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

Learn more about our Design Apprentice Program

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Step into the intersection of engineering and data science at Shopify as a Search Relevance Engineer. You'll be designing and implementing AI-powered search and discovery solutions that empower our merchants and revolutionize their experiences. In a role that thrives on change and mastery, you'll push the boundaries of what's possible, crafting tangible solutions that make a real difference in the daily lives of entrepreneurs.

Key Responsibilities:

• Collaborate with data scientists and engineers to productionize data products through load testing, metrics analysis, and experimentation.
• Design and implement features to enhance search and recommendation relevance, including semantic search, query understanding, and personalization.
• Build and maintain data pipelines for information retrieval systems.
• Tune queries that power search and discovery experiences.
• Develop tools for evaluation and relevance engineering, adhering to high-quality software engineering practices.
• Prioritize and communicate effectively with both technical and non-technical audiences.
• Mentor engineers and data scientists.

Qualifications:

• Mastery of relevance engineering, with experience in discovery and recommendation systems powered by Elasticsearch, Solr, Lucene, or vector databases.
• Extensive experience using Python, with a strong grasp of object-oriented programming (OOP) fundamentals.
• Ability to write efficient, optimized code with low latency requirements.
• Strong software development background, with proven problem-solving skills and technical system thinking.
• Experience in training, evaluating, testing, and deploying machine learning, natural language processing, or generative AI products at scale is a plus.
• Familiarity with statistical methods like regression, GLMs, or experiment design and analysis is welcome.
• Exposure to other languages such as Ruby, Rails, Rust, or Typescript is advantageous.
• This role may require on-call work.

*At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.

This role may require on-call work. Ready to join a team of driven crafters building world-class search and discovery experiences? Join us and make commerce better for everyone.*

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Senior Software Engineer- Streaming Pipelines

• Remote - Americas
• Engineering & Data

Apply Now

About the role

Looking for a Senior Software Streaming Pipelines Engineer to join our team reimagining how merchant data flows through modern streaming architectures. This isn’t your typical ETL role – you’ll be crafting solutions that challenge conventional approaches to data processing at global scale.

What makes this exciting?

• We’ve developed a declarative pipeline framework using Apache Beam, Google Cloud Dataflow, and ClickHouse that transforms how data engineers build streaming systems. Imagine YAML-driven pipelines that eliminate boilerplate code, real-time stream processing across multiple regions, and an architecture that makes complex data transformations feel effortless.
• You’ll work across multiple languages – Kotlin, Ruby, Python, and Rust – choosing the right tool for each challenge, alongside dbt for elegant data modelling and our custom framework that turns pipeline development into a configuration exercise rather than a coding marathon.
• The puzzle? Replacing entrenched batch systems with streaming-first architecture while merchants never notice the transition.
• You’ll tackle fascinating problems: How do you handle late-arriving data in distributed streams? What’s the most elegant approach to backfill terabytes while maintaining real-time processing? How do you architect lightning-fast real-time modelling that seamlessly combines data from multiple tables?
• We embrace AI and LLMs to accelerate repetitive tasks, freeing you to focus on the creative problem-solving that makes this work truly rewarding.

If you love turning “impossible” requirements into beautiful solutions, this is your playground.

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

Apply Now

Application

*Required

Name*

Email*

Resume*

Linkedin Profile*

Location*

Start typing and select a location from the dropdown.

Do you now or in the future require sponsorship to work in the country of employment?

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

Please confirm you've read and agree with our candidate NDA*

NDA here

Please confirm you've read our applicant privacy notice*

Privacy notice here

Please confirm if you agree to your Shopify interview(s) being recorded and transcribed to help improve our hiring process. Agreeing/not agreeing to recording has no impact on our hiring decision.

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

Learn more about our Design Apprentice Program

• Terms of Service
• Privacy Policy

About the role

Join Shopify's dynamic engineering team, where code is core and innovation drives commerce forward. As a Senior Staff Engineer on the Measurement team, you'll lead the development of cutting-edge marketing analytics tools that empower merchants to optimize customer acquisition and maximize return on ad spend. Collaborate with data engineers, product teams, and partners to build unbiased insights, integrations, and reports that analyze paid advertising performance. Help shape the future of e-commerce analytics in a fast-paced environment, solving complex attribution challenges to make data-driven decisions accessible for entrepreneurs worldwide.

Key Responsibilities:

• Design scalable data pipelines for marketing analytics and attribution models measuring ad impact.
• Build integrations with partners (e.g., Google, Meta, Pinterest, TikTok) for real-time ad data processing.
• Develop analytics systems using streaming tech like Flink and Kafka for large datasets and timely insights.
• Own end-to-end delivery of measurement tools, from prototyping to production APIs and reports.
• Optimize data processing efficiency with SQL, ClickHouse, and analytics for fast query latencies.
• Influence product roadmap and advocate strategic direction with executive stakeholders.
• Evolve measurement infrastructure for emerging paradigms like multi-touch attribution and AI metrics.
• Mentor engineers and collaborate on unbiased insights to optimize merchant ad strategies.

Qualifications:

• Proven data engineering experience building scalable analytics systems.
• Strong skills in streaming tech like Apache Flink, Spark, and Kafka for real-time processing.
• Expertise in analytics, attribution modeling, and marketing/e-commerce metrics.
• Experience with APIs for data integrations and strong SQL proficiency.
• Ruby is a plus but not required.
• Skills in performance optimization for data pipelines and large datasets.
• Strong collaboration with teams like data scientists and product managers.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.

This role may require on-call work.

Ready to craft the world’s best marketing analytics tools and drive data-powered commerce forward? Join us and make commerce better for everyone.

Back

Engineering Manager - Real Time Analytics

• Remote - Americas
• Engineering & Data

Apply Now

About the role

We’re Building the Future of Real-Time Merchant Analytics at Shopify!

Looking for a Senior Software Streaming Pipelines Engineer and an Engineering Manager to join our team reimagining how merchant data flows through modern streaming architectures. This isn’t your typical ETL role – you’ll be crafting solutions that challenge conventional approaches to data processing at global scale.

What makes this exciting?

• We’ve developed a declarative pipeline framework using Apache Beam, Google Cloud Dataflow, and ClickHouse that transforms how data engineers build streaming systems. Imagine YAML-driven pipelines that eliminate boilerplate code, real-time stream processing across multiple regions, and an architecture that makes complex data transformations feel effortless.
• You’ll work across multiple languages – Kotlin, Ruby, Python, and Rust – choosing the right tool for each challenge, alongside dbt for elegant data modelling and our custom framework that turns pipeline development into a configuration exercise rather than a coding marathon.
• The puzzle? Replacing entrenched batch systems with streaming-first architecture while merchants never notice the transition.
• You’ll tackle fascinating problems: How do you handle late-arriving data in distributed streams? What’s the most elegant approach to backfill terabytes while maintaining real-time processing? How do you architect lightning-fast real-time modelling that seamlessly combines data from multiple tables?
• We embrace AI and LLMs to accelerate repetitive tasks, freeing you to focus on the creative problem-solving that makes this work truly rewarding.

If you love turning “impossible” requirements into beautiful solutions, this is your playground.

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

Apply Now

Application

*Required

Name*

Email*

Resume*

Linkedin Profile*

Location*

Start typing and select a location from the dropdown.

Do you have the right to work in your listed location?

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

Which category best describes your engineering expertise?*

BackendFrontendFull StackInfrastructureMobileSecurityApplied Machine Learning

How many years of experience do you have managing engineering teams? This does not include academic experience or internships.*

0-4 years5-7 years8-10 years11+ years

Please select the tools and technologies that you are proficient in.*

Ruby on RailsRustGolangRemixPythonJavaScalaTypeScriptReact NativeSwiftKotlinJavaScriptReactHTML/CSSGraphQL

Engineering Managers at Shopify are highly technical, and coding proficiency is critical to success in this role. As part of our hiring process, candidates are required to participate in two separate 75-minute Pair Programming interviews at different stages of the process (in addition to other technical assessments), where you will take the lead on solving technical problems. These sessions allow us to assess your problem-solving abilities, coding skills, and hands-on technical craft. Are you comfortable with being invited to participate in two Pair Programming interviews as part of your evaluation?*

Heck yes, that's why I'm here!I'm cool with itI'm a little unsure about itNah

Preferred programming language for interviews?*

Please give an example of a project where you led the team . We’d love to know things like what the project was, what part you played, what the outcome was and what you’d change. (Plus, any other details you’d like to share!)*

What technology or tool have you been tinkering with lately?

Please confirm you've read and agree with our candidate NDA*

NDA here

Please confirm you've read our applicant privacy notice*

Privacy notice here

Please confirm if you agree to your Shopify interview(s) being recorded and transcribed to help improve our hiring process. Agreeing/not agreeing to recording has no impact on our hiring decision.*

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

Learn more about our Design Apprentice Program

• Terms of Service
• Privacy Policy

Back

Infrastructure Engineers

• Remote - Americas
• Engineering & Data

Apply Now

About the role

Infrastructure engineers build and develop the blocks that move all of Shopify forward. It's basically building the infrastructure that powers the infrastructure for commerce [aka Shopify]. They handle absurdly high amounts of traffic [think: millions of requests per second] and deliver performant, resilient and seamless shopping experiences for everyone, everywhere.

At Shopify, every developer is expected to spend the majority of their time coding. Working on infrastructure doesn't mean just managing it; it means actually writing code to build and improve the infrastructure.

Key Responsibilities

• Write code to build and maintain infrastructure that supports millions of transactions during global peak shopping periods
• Design and optimize high-performance systems that push technology to its limits and handle critical workloads
• Develop comprehensive monitoring and observability solutions to ensure system reliability and performance
• Build scalable data infrastructure that powers commerce experiences for merchants and customers worldwide

Qualifications

• Strong expertise in infrastructure engineering with proven coding experience building scalable systems
• Proficiency with containerization and orchestration using Kubernetes, Docker, and infrastructure-as-code with Terraform
• Experience with monitoring and observability platforms, particularly Prometheus and related tooling
• Hands-on experience with distributed systems technologies including Kafka, MySQL, Redis, and cloud platforms like GCP

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.

This role may require on-call work

Ready to build the backbone of Shopify? Join the team that's making commerce better for everyone.

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

Apply Now

Application

*Required

Name*

Email*

Location*

Start typing and select a location from the dropdown.

Resume*

Linkedin Profile

Alternative Link

If you've contributed to the largest open-source projects, optimized systems to handle unprecedented traffic, or developed game-changing algorithms, we want to know about it. Link your highlights and skip the resume.

Message to hiring manager:

Do you now or in the future require sponsorship to work in the country of employment?

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

How many years of hands-on  experience do you have in infrastrucure or engineering? This does not include academic experience or internships.*

0-4 years5-7 years8-10 years11+ years

Please select the tools and technologies that you are proficient in.*

Ruby on RailsRustGolangRemixPythonJavaScalaTypeScriptReact NativeSwiftKotlinJavaScriptReactHTML/CSSGraphQLSQLRelational DatabasesNon Relational DatabasesElasticsearch/SolrFlinkBazelKafkaRedisKubernetesGCPAWSSplunkOpen SourceSite Reliability EngineeringDevOpsReliabilityGKETerraformService DiscoveryInfrastructure as CodeCaching

As an Engineer, how would you describe your experience on infrastructure  or engineering projects?*

I haven't led a project yet, but I've contributed to the tasks assigned to me and learned from the process.I've led a small project or a part of a larger project from start to finish.I've led multiple projects across teams and stakeholders, and was accountable for the project's success.I've led high-stakes projects spanning multiple stakeholders, disciplines, and technical complexities.

Describe your involvement in the design and architecture of infrastructure or engineering projects in your current role.*

I've implemented features based on existing designs and learned from the process.I've contributed to the design and architecture of components or features within a larger application.I've led the design and architecture of entire applications or significant parts of complex systems.I've been responsible for the design, architecture, and delivery of multiple complex, large-scale systems.

As an Engineer, how would you describe your approach to mentorship?

I'm still learning the ropes, so I focus more on learning myself, rather than mentoring others.I'm comfortable with my skills, but I haven’t done any official mentoring.I actively mentor less experienced engineers, sharing my knowledge and often lead team discussions.I am a craft mentor across the organisation, and am often consulted on high-level decisions.

What professional experience do you have managing infrastructure at scale?*

Share an example of how you've contributed to the design and development of an infrastructure platform?*

What automation tools have you used to manage infrastructure?*

What technology or tool have you been tinkering with lately?*

Please confirm you've read and agree with our candidate NDA*

NDA here

Please confirm you've read our applicant privacy notice*

Privacy notice here

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

Learn more about our Design Apprentice Program

• Terms of Service
• Privacy Policy

Back

Data Engineers

• Remote - Americas
• Engineering & Data

Application

*Required

Name*

Email*

Location*

Start typing and select a location from the dropdown.

Resume

Linkedin Profile

Alternative Link

If you've contributed to the largest open-source projects, optimized systems to handle unprecedented traffic, or developed game-changing algorithms, we want to know about it. Link your highlights and skip the resume.

Message to hiring manager:

Do you have the right to work in your listed location?

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

How many years of professional experience do you have in data engineering, not including academic experience and internships?*

0-3 years3-5 years5-7 years7-10 years10+ years

As a Data Engineer, how would you describe your approach to mentorship?*

I'm still learning the ropes, so I tend to focus more on absorbing knowledge myself.I'm comfortable with my skills, but I still rely on more experienced engineers for complex problems.I mentor others and promote a culture of learning and growth within the organization.I mentor others, and play a role in increasing the technical competencies of my craft at the org level.

As a Data Engineer, how would you describe your experience on projects?*

I haven't led a project yet, but I've contributed to the tasks assigned to me and learned from the process.I've led a small project or a part of a larger project from start to finish.I've led multiple projects across teams and stakeholders, and was accountable for the project's success.I've led high-stakes projects spanning multiple stakeholders, disciplines, and technical complexities.

Describe your experience with data architecture and modeling concepts in your current or previous roles.*

I have contributed to building data models within a data warehouse, with a clear and defined scope.I've contributed to and led data modeling and design within a data warehouse, with an ambiguous scope.I've led data modeling and design for complex concepts within a data warehouse frameworkI regularly lead the design and modeling of complex, large-scale data warehouse systems.

As a Data Engineer, what area would you prioritize for your main focus, aligning with your expertise and interest?*

Bringing data onto or from a data platform (ETL/ELT), managing API interactions, and monitoring pipelines.Building tooling and frameworks crucial for data processing and exposure, and creating custom software.Data modeling, incorporating intricate business logic, and constructing a robust data warehouse.Streaming data pipelines, delivering real-time data transport solutionsData science and analytics, constructing data marts for in-depth data analysis, and serving the business.

Please confirm you've read and agree with our candidate NDA*

NDA here

Please confirm you've read our applicant privacy notice*

Privacy notice here

Share an AI-assisted or vibe-coded work sample (optional)

Want to stand out? Optionally share something you’ve made with an AI tool — e.g. a “sell yourself” build, a short project, or a creative take on your background — that shows why we should consider you and how you work with AI. We’re interested in your taste, effort, and the quality of what you produce. Submit a link, paste your code or output, or attach a file. Not required to apply.

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

Learn more about our Design Apprentice Program

• Terms of Service
• Privacy Policy

At Shopify, Engineering Managers drive impact by giving engineers the direction, support, and coaching needed to excel in our Ruby and Rails ecosystem. As the largest Ruby and Rails shop in the world, we're looking for passionate leaders who can combine technical expertise with people leadership to scale the foundational pieces of Shopify's commerce infrastructure.

You'll lead a team of Ruby and Rails experts tackling complex problems that impact not only millions of merchants worldwide, but also the Ruby and Rails open source community.

About the Team

Shopify’s Ruby and Rails Infrastructure team exists to ensure that Ruby and Rails are 100-year tools that will continue to merit being Shopify’s toolchain of choice. Our goal is to be stewards of the language and ecosystem, both within Shopify and within the open source community.

Ruby and Rails Infrastructure is split into three subteams, each of which operates in its own domain:

• Ruby Infrastructure works on making sure the Ruby language continues scaling at Shopify by contributing to the performance, stability and evolution of the language and its implementation internally and upstream.
• Rails Infrastructure are stewards of Rails within Shopify, and work on improving Shopify’s usage of Rails internally and contributing improvements back to the framework and ecosystem.
• Ruby Developer Experience aims to deliver an opinionated and state-of-the-art Ruby development experience to Shopify and the Ruby community.

On Ruby and Rails Infrastructure, your teammates will be Ruby and Rails experts from around the world, including members of both the Ruby Core Committers and Rails Core teams.

Recent projects include building a new just-in-time compiler for Ruby, a better frontend for Ruby type checking, and a new structured logger for Rails.

Key Responsibilities

In this role, your day-to-day responsibilities will include:

• Managing a team of 6-12 individual contributors while working alongside 3 peer managers and reporting to the group's director.
• Solving cutting-edge language and framework problems while scaling the largest Rails application in the world.
• Collaborating with tech leads to make impactful decisions about how we scale the Ruby language, Rails framework, and our applications to support global commerce.
• Balancing technical contributions with people management and leadership responsibilities.
• Coaching and growing developers passionate about Ruby and Rails, helping maintain a high-performing team in Shopify’s unique remote-first environment.
• Ensuring the team works at the right level of the stack—whether internal to Shopify or in the broader Ruby and Rails ecosystem.
• Partnering with product teams to align language and framework investments with meaningful business outcomes
• Recruiting and hiring excellent candidates to grow the Ruby and Rails Infrastructure team.

What You Bring

• Engineering management experience
• You are excited about AI and how it will transform how we write code in the next year and beyond.
• Deep technical expertise in programming language internals or web framework development OR substantial experience managing teams with this kind of expertise

• Examples of relevant technical experience include:

• Implementing language internals such as parsers, compilers, interpreters, or runtimes

• Designing and implementing type systems
• Developing web application frameworks (Rails, Django, etc.)
• Building developer tools such as language servers, linters, or other static analysis tools
• Experience with Ruby and/or Ruby on Rails is preferred, but we welcome candidates with comparable depth in other languages and frameworks

Nice to Have

• Experience writing Ruby and Rails code, especially in large-scale production environments
• Experience contributing to Ruby, Rails, or related open-source projects
• History of technical writing or speaking about Ruby and Rails related topics
• Experience managing remote or globally distributed engineering teams

At Shopify, we move quickly—our hiring process aims to complete the entire interview loop within 30 days, including a pair programming interview where you'll demonstrate your Ruby expertise.

Join us in our mission to make commerce better for everyone while advancing the Ruby and Rails ecosystem for developers worldwide.

Join Shopify's dynamic engineering team, where code is core and innovation drives commerce forward. As a Java Search Infrastructure Engineer, you'll build distributed systems that power search query serving across billions of products. Collaborate with platform engineers and SREs to create scalable, resilient search infrastructure that helps merchants succeed at the infinite game of entrepreneurship.

Key Responsibilities:

• Build high-throughput scatter-gather systems that coordinate queries across hundreds of shards and aggregate results efficiently.
• Own search APIs end-to-end—interface design, load balancing, circuit breaking, and graceful degradation.
• Optimize networking and JVM performance—connection pooling, request batching, GC tuning, and profiling for high-load scenarios.
• Design comprehensive observability through structured logging, metrics, and distributed tracing.
• Build A/B testing frameworks enabling data-driven experimentation at scale.
• Solve distributed systems challenges—consistency, availability, latency tail tolerance, and failure handling.

Qualifications:

• Proven expertise in Java for building production distributed systems at scale.
• Experience with search infrastructure, particularly scatter-gather patterns and distributed query execution.
• Networking expertise—HTTP/2, TCP tuning, connection management, protocol design.
• Experience with service frameworks—Thrift, gRPC, or similar RPC frameworks.
• Observability expertise—building logging pipelines, metrics infrastructure, distributed tracing.
• Load balancing and A/B testing experience—consistent hashing, adaptive routing, experiment design.
• Strong collaboration skills, working with cross-disciplinary teams including platform engineers and data scientists.

*At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.

This role may require on-call work. Ready to craft the world’s best product search and drive AI-powered commerce forward? Join us and make commerce better for everyone.*

Back

Data Engineers

• Remote - Americas
• Engineering & Data

Apply Now

About the role

Build the data systems that power global commerce. As a Data Engineer at Shopify, you'll architect pipelines that transform complex information into valuable insights. Your work will shape our technical direction and help millions of merchants make smarter decisions. Whether optimizing data models or creating new analytics tools, your expertise drives what's possible here. Ready to solve challenges that matter?

Key Responsibilities:

• Design and implement scalable models and pipelines that drive insights and innovation.
• Transform raw information into intelligence to support merchant success and excellence.
• Collaborate closely with product teams to ensure quality and integrity across platforms.
• Optimize workflows and infrastructure to enhance performance and scalability.
• Lead efforts in peer-reviewing and standardizing practices to uphold benchmarks.

This role may require on-call work.

Qualifications:

• Extensive data modeling experience, utilizing various paradigms and techniques.
• Strong analytical skills and experience with visualization tools.
• Proficiency with SQL, Python, and relevant technologies.
• Experience with batch transformation and warehouse layers on cloud platforms such as AWS, GCP, or Azure.
• Proven ability to translate complex information into strategic insights while working effectively with teams.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days.

Ready to turn raw data into product gold? Join the team that’s making commerce better for everyone.

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

Apply Now

Application

*Required

Name*

Email*

Location*

Start typing and select a location from the dropdown.

Resume

Linkedin Profile

Alternative Link

If you've contributed to the largest open-source projects, optimized systems to handle unprecedented traffic, or developed game-changing algorithms, we want to know about it. Link your highlights and skip the resume.

Message to hiring manager:

Do you have the right to work in your listed location?

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

How many years of professional experience do you have in data engineering, not including academic experience and internships?*

0-3 years3-5 years5-7 years7-10 years10+ years

As a Data Engineer, how would you describe your approach to mentorship?*

I'm still learning the ropes, so I tend to focus more on absorbing knowledge myself.I'm comfortable with my skills, but I still rely on more experienced engineers for complex problems.I mentor others and promote a culture of learning and growth within the organization.I mentor others, and play a role in increasing the technical competencies of my craft at the org level.

As a Data Engineer, how would you describe your experience on projects?*

I haven't led a project yet, but I've contributed to the tasks assigned to me and learned from the process.I've led a small project or a part of a larger project from start to finish.I've led multiple projects across teams and stakeholders, and was accountable for the project's success.I've led high-stakes projects spanning multiple stakeholders, disciplines, and technical complexities.

Describe your experience with data architecture and modeling concepts in your current or previous roles.*

I have contributed to building data models within a data warehouse, with a clear and defined scope.I've contributed to and led data modeling and design within a data warehouse, with an ambiguous scope.I've led data modeling and design for complex concepts within a data warehouse frameworkI regularly lead the design and modeling of complex, large-scale data warehouse systems.

As a Data Engineer, what area would you prioritize for your main focus, aligning with your expertise and interest?*

Bringing data onto or from a data platform (ETL/ELT), managing API interactions, and monitoring pipelines.Building tooling and frameworks crucial for data processing and exposure, and creating custom software.Data modeling, incorporating intricate business logic, and constructing a robust data warehouse.Streaming data pipelines, delivering real-time data transport solutionsData science and analytics, constructing data marts for in-depth data analysis, and serving the business.

Please confirm you've read and agree with our candidate NDA*

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Please confirm you've read our applicant privacy notice*

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Share an AI-assisted or vibe-coded work sample (optional)

Want to stand out? Optionally share something you’ve made with an AI tool — e.g. a “sell yourself” build, a short project, or a creative take on your background — that shows why we should consider you and how you work with AI. We’re interested in your taste, effort, and the quality of what you produce. Submit a link, paste your code or output, or attach a file. Not required to apply.

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

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Product Data Scientists

• Remote - Americas
• Engineering & Data

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About the role

Are you ready to decode commerce through the power of data? As a Product Data Scientist at Shopify, you'll deeply understand our products, telling their stories and figuring out how to make them 10x better. You’ll own big problems and collaborate with cross-functional partners to build data-informed solutions. You'll be the architect of insights that guide our product journey, helping determine what we build and how we build it.

Key Responsibilities:

• Unearth insights through advanced analytics and data exploration to inform product strategy and development.
• Partner with product managers and engineers to translate complex datasets into actionable business strategies.
• Apply statistical models, regression analysis, segmentation techniques, and experimental methods to optimize product performance.
• Build powerful data products that improve the experience of merchants (and more) worldwide.
• Influence decision-making processes by providing clear, data-backed recommendations.
• Continuously innovate by leveraging AI tools and cutting-edge analytics techniques.

Qualifications:

• Strong understanding of SQL and other data tools such as dbt.
• Proficiency in programming languages such as Python, and experience with data visualization tools.
• Proven experience in statistical analysis, data modeling, and machine learning.
• Skilled in translating complex data into actionable insights for stakeholders.
• Ability to own and solve complex product and business problems with data.
• Experience with cloud platforms and big data technologies is a plus.
• Demonstrated ability to thrive in a fast-paced, dynamic environment.

Ready to transform data into groundbreaking product discovery? Join the team that's making commerce better for everyone.

About Shopify

Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now.

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If you've contributed to the largest open-source projects, optimized systems to handle unprecedented traffic, or developed game-changing algorithms, we want to know about it. Link your highlights and skip the resume.

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Do you have the right to work in your listed location?*

Which track are you interested in pursuing with Shopify?*

Individual ContributorPeople Manager

What is your level of experience using SQL for data manipulation?*

I have no experience working with SQL and am unfamiliar with applying basic SQL transformations.I use basic SQL transformation (joins, filters, aggregations) to solve straightforward business questions.I have an understanding of data-warehouses, and use SQL to manipulate dimension and facts tables to solve business questions.I have an understanding of data-warehouses, and I use advanced SQL techniques (window statements, complex joins, arrays) to solve complex business questions.

What is your level of experience with Python and general programming principles?*

I have no experience with Python or general programming principlesI have some experience with Python and can write code to solve simple problems.I have an understanding of programming principles (if statements, loops, basic data structures, functions) and am able leverage libraries to solve problems in a scripting/notebooks setting.I have an understanding of programming paradigms (such as object orientation) and apply software engineering best practices to solve complex problems.

How many years of hands-on Data Science experience do you have? This does not include academic experience or internships*

0-4 years5-7 years8-10 years11+ years

As a Data Scientist, how would you describe your approach to mentorship?*

I'm still learning the ropes, so I tend to focus more on absorbing knowledge myself.I'm comfortable with my skills, but I still rely on more experienced engineers for complex problems.I mentor others and promote a culture of learning and growth within the organization.I mentor others, and play a role in increasing the technical competencies of my craft at the org level.

As a Data Scientist, how would you describe your experience on projects?*

I haven't led a project yet, but I've contributed to the tasks assigned to me and learned from the process.I've led a small project or a part of a larger project from start to finish.I've led multiple projects across teams and stakeholders, and was accountable for the project's success.I've led high-stakes projects spanning multiple stakeholders, disciplines, and technical complexities.

Which of the following best describes your most recent role in a product decision?*

I've executed tasks that were defined for me within a well defined scope.I executed tasks on complex projects where the results influenced product direction in the short termI led the delivery of work on a complex project, that impacted the overall product road map.I led the delivery of complex projects, spanning multiple stakeholders, with long-term product impact.

What is your level of familiarity with research design and experimentation?*

I form and disprove hypotheses based on a given business problem using basic statistical techniques.I run experiments and leverage advanced techniques to make actionable recommendations to my team.I use experiments + advanced statistical techniques to drive cross-functional product decisions.I explore new methodologies to answer complex business questions, and influence the craft of data science.

Tell us about an interesting metric you defined and presented in a professional capacity, and the impact of that work.*

Tell us about a difficult stakeholder situation at work, and how you managed it.*

Share a technical problem you solved at work, the tools you used to solve it, and the outcome of that.*

Please confirm you've read our applicant privacy notice*

Privacy notice here

Please confirm you've read and agree with our candidate NDA*

NDA here

Share an AI-assisted or vibe-coded work sample (optional)

Want to stand out? Optionally share something you’ve made with an AI tool — e.g. a “sell yourself” build, a short project, or a creative take on your background — that shows why we should consider you and how you work with AI. We’re interested in your taste, effort, and the quality of what you produce. Submit a link, paste your code or output, or attach a file. Not required to apply.

Work with us in your early career

Dev Degree Program

A 3-4-year program that allows people to earn a computer science degree while working. It’s designed for those looking to break into computer science or transition into the tech field.

Learn more about our Dev Degree Program

Internship Program

Shopify offers 4-month paid Engineering internships that are open to students, recent graduates, and those early in their careers.

Learn more about our Internship Program

APM Program

Shopify’s 12-month Apprentice Product Manager program is designed to help you gain the skills needed to start a product management career.

Learn more about our APM Program

Design Apprentice Program

Shopify's 12-month Design Apprentice Program pairs early-career designers with senior mentors through two rotations. Built for new graduates, career switchers, and those early in their design careers.

Learn more about our Design Apprentice Program

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The driver’s seat is a hot seat. Engineering Managers drive impact by giving engineers the direction, support, and coaching needed to ship the thing, and ship it fast. This isn’t about herding. Managers are there to make great decisions about product development that impact millions of users daily in the process. Every piece of the rocketship counts.

We expect our managers to be masters of the craft and be able to go deep into the details, mastering the fundamentals and honing their skills. Cavalry officers must be able to ride horses. You have a deep love for the craft and have discovered the greatest impact you can make is through leading others. At the same time, you still enjoy getting your hands dirty, coding for fun or on the weekends.

Why You’ll Love Working at Shopify:

• Empowerment at Scale: Make impactful decisions that shape the future of commerce for millions of merchants worldwide.
• Innovative Environment: Lead teams working on cutting-edge projects, from AI-driven translation tools to resilient data platforms and streaming services.
• Growth Opportunities: Cultivate your leadership skills while mentoring engineers and driving their professional development.
• Community and Culture: Be part of a diverse and inclusive work environment that values creativity, collaboration, and continuous learning.

Key Responsibilities:

• Lead and Inspire: Guide and support elite engineering teams passionate about building innovative infrastructure solutions.
• Drive Impactful Decisions: Oversee the development and execution of strategic projects, making critical decisions that affect product development and user experience.
• Cultivate Technical Excellence: Foster a culture of innovation, collaboration, and continuous improvement within your team, ensuring high performance and accountability.
• Hands-On Leadership: Stay engaged in technical designs and product development, maintaining a balance between management responsibilities and hands-on contributions.
• Cross-Functional Collaboration: Work closely with product managers, data teams, and other stakeholders to align on project goals and deliverables.

What You Bring:

• Proven experience as a technical lead or manager, with a track record of building and leading high-performing engineering teams.
• Strong technical background in software development or infrastructure management, with expertise in relevant technologies.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
• A passion for mentoring and developing talent, with a focus on fostering a positive team culture.
• Experience with shipping weekly and a commitment to delivering high-quality results.

Nice to Have:

• Familiarity with cloud technologies, data engineering, or large-scale systems.
• Experience in driving technical projects from concept to completion.
• Knowledge of performance engineering, load testing, or resilience engineering practices.

If you are excited about leading high-performing teams and making a significant impact, we want to hear from you! Join us in our mission to make commerce better for everyone.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.

This role may require on-call work

At Shopify, data isn't just numbers—it's the voice of our merchants, buyers, and developers. Listening to this voice is key to revolutionizing commerce for everyone. Our Data Engineering team constructs the essential frameworks that convert raw data into trusted, actionable insights, which not only drive decision-making but also power our operational systems, such as cutting-edge recommender engines and efficient order processing systems.

We’re on the lookout for Data Engineering Manager to lead and inspire a team of Data Engineers who build and maintain the robust infrastructure, pipelines, and data models that fuel Shopify's growth. Your mission? Ensure your teams not only meet objectives but thrive in an environment that promotes growth and mastery of their craft.

What You'll Do

• Lead a team (or multiple teams) of Data Engineers, steering multiple projects within a data domain
• Guarantee team objectives are met, resources are optimized, and your people are empowered
• Champion technical excellence across our cutting-edge stack: Flink, BigQuery, dbt, Kafka, Spark, Airflow
• Collaborate with Product, Engineering, and leadership to craft high-impact data solutions while synchronizing your teams’ efforts with Shopify’s strategic vision
• Cultivate top talent: we treat data products like real products, with ownership, reliability, and quality at the core
• Own delivery outcomes: ensure projects launch on time and exceed quality benchmarks
• Champion data governance, dimensional modeling, and best practices across data pipelines
• Foster a culture of craft excellence, knowledge sharing, and relentless improvement

What We're Looking For

• Proven experience in managing and scaling Data Engineering teams
• Hands-on expertise with data infrastructure, including ETL/ELT pipelines, data modeling, operational systems, and distributed systems
• Strong command of modern data stack technologies (e.g., Spark, dbt, Airflow, BigQuery, Kafka, or similar)
• Deep understanding of data transformation logic beyond tool configuration
• Ability to link team efforts to business outcomes and make strategic trade-offs
• A track record of developing engineers and building high-performing teams
• Stellar collaboration skills across technical and non-technical spheres
• You thrive in fast-paced environments and embrace ambiguity while maintaining focus on data quality, governance, and lineage
• Experience with large-scale data architecture, including domain-driven design and data governance

Are you ready to lead the charge? Join a team where data isn't just a function, it's a catalyst for change. At Shopify, you'll be at the forefront of revolutionizing commerce globally, steering innovation through data. If you're passionate about building the future and thrive on turning complex challenges into transformative solutions, we want you on board. Let's make commerce better for everyone.