Software Engineer III

JPMorgan Chase

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Wilmington, DE
Posted: 29 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $171k

$115k most similar roles pay here $217k

This listing doesn't post a salary. Most similar roles pay $135,737–$207,250.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Software Engineer III

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As a Software Engineer III - Databricks within the Corporate Sector's Enterprise Technology team, you will serve as a seasoned member of an agile team designing and delivering secure, stable, and scalable technology products. You are responsible for providing technical leadership in design, development, and troubleshooting while establishing engineering standards. Your daily work involves writing high-quality code in Python or Java, building data pipelines using Databricks ETL, and productionizing cloud-based ML pipelines. You will manage MLOps workflows, coordinate infrastructure changes with SRE teams, and utilize SDLC automation to improve delivery velocity. Key technologies include Databricks features like Delta Lake and Unity Catalog, PySpark, Kafka, Terraform, Kubernetes, and AWS services such as SageMaker and Lambda. You will also leverage enterprise-authorized AI coding tools while ensuring security across the machine learning lifecycle and data processing workflows.

What does a Software Engineer earn?

Median $197500 from 2196 postings across 133 companies.

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Skills

Databricks Python Java SQL PySpark AWS SageMaker EMR Lambda EC2 Kubernetes Terraform Kafka Oracle Cassandra MLOps CI/CD Delta Lake Unity Catalog TensorFlow Pandas NumPy

What you'll do

Provide technical leadership in the design, development, and troubleshooting of complex multi-domain solutions.
Write secure, high-quality code in Python or Java while mentoring others on code quality.
Build and manage data pipelines using Databricks ETL tools.
Develop and productionize cloud-based machine learning pipelines for deployment and operationalization.
Manage MLOps workflows to ensure resiliency, observability, and security across the ML lifecycle.
Implement SDLC tooling and automation to improve delivery velocity through CI/CD and cloud-native practices.
Translate business requirements from stakeholders into scalable technical solutions.
Utilize enterprise-authorized AI coding tools to generate code, refactor logic, and create unit tests.

What we're looking for

Formal training or certification on software engineering concepts and 3+ years of applied experience.
Hands-on experience in software engineering, system design, application development, testing, and operational stability.
Proficiency in Python and a strong grounding in secure data practices.
Hands-on Databricks experience across Delta Lake, Unity Catalog, Workflows, Repos/notebooks, SQL Warehouses, and cluster optimization.
Cloud engineering experience building ML pipelines and deploying models using AWS services like ECS, EMR, Lambda, EC2, and SageMaker.
Experience with PySpark, Kafka, Terraform, and Kubernetes for data processing, streaming, IaC, and container orchestration.
Database experience with Oracle and/or Cassandra.
Familiarity with CI/CD, application resiliency, security best practices, Agile/Scrum methodologies, and SDLC automation tools.
Experience using enterprise-authorized AI-assisted software development tools to create, validate, and refine outputs for correctness and security.
Background with machine learning frameworks, MLOps practices, and end-to-end ML lifecycle management (preferred).
Experience with the Python ML ecosystem (pandas, NumPy) and Databricks for data engineering at scale (preferred).
Experience with ERWIN for data modeling (preferred).
Familiarity with TensorFlow (preferred).
Familiarity with data modeling and query optimization (preferred).

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