Operations Data Engineer

Apple Inc

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Work type
On-site
Location
Austin, TX
Posted
15 days ago
Freshness
Confirmed live today

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How this pay compares to similar roles

Similar $163k
$116k most similar roles pay here $210k

This listing doesn't post a salary. Most similar roles pay $126,800–$199,100.

Based on 240 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3513 open roles on FindRole.

Listed pay typically runs $165,800–$277,600 across 2730 roles with salary data.

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At a glance

TL;DR · Operations Data Engineer

Operations Data Engineer The Operations Data Engineer joins the team to design and build modern, scalable data infrastructure that powers analytics, machine learning, and AI-driven decision-making across supply chain operations. You will translate business requirements into robust engineering solutions by designing end-to-end pipelines for batch and real-time streaming workloads. Key responsibilities include building high-quality data models using dbt, managing workflows with Apache Airflow, and implementing data observability and lineage tracking. You will collaborate with cross-functional teams to operationalize models and manage cloud-native environments including Snowflake, Spark, Delta Lake, and Apache Iceberg. The role requires expertise in Python, SQL, Kafka, Flink, and Docker/Kubernetes. Additionally, you will leverage AI-assisted development tools and LLM-powered agents to automate pipeline authoring while optimizing query performance and storage for large-scale data at scale within the supply chain domain.

What you'll do

  • Translate business requirements into robust, scalable engineering solutions for operations decision-making.
  • Design and implement end-to-end data pipelines for both batch and real-time streaming workloads.
  • Build and maintain high-quality data models using modern transformation frameworks like dbt.
  • Architect and operate data workflows using orchestration tools with integrated monitoring and alerting.
  • Implement data observability, lineage tracking, and validation frameworks to ensure data integrity.
  • Manage cloud-native data environments including Snowflake, Spark, and Delta Lake/Apache Iceberg.
  • Apply DataOps principles such as CI/CD, version control, and containerization to deliver production-grade products.
  • Utilize AI-assisted development tools and LLM-powered agents to accelerate pipeline authoring and code generation.

What we're looking for

  • MS in Computer Science, Data Engineering, Statistics, Applied Math, Data Science, Operations Research, or a related field and 8+ years of experience.
  • BS in a related field and 10+ years of hands-on industry experience.
  • Domain expertise in supply chain, operations management, logistics, planning & forecasting, production integration, and channel management.
  • Expertise building large-scale ETL/ELT pipelines using Python, SQL, dbt, Spark, and Kafka or Flink for streaming.
  • Proficiency with cloud data platforms like Snowflake and open table formats such as Delta Lake or Apache Iceberg.
  • Experience with workflow orchestration tools (Apache Airflow), data quality frameworks, observability tooling, and data lineage tracking.
  • Experience implementing GenAI and Agentic AI tooling, including LLM-assisted code generation and AI-powered data pipeline automation.
  • Experience with data visualization and self-service analytics platforms like Tableau, Streamlit, or ThoughtSpot.

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