Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Data Engineer at JPMorgan Chase within the Commercial and Investment Banking, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies
• Adds to the team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training in software engineering concepts and 10+ years of applied experience.
• Extensive experience building and operating AWS/public cloud–based applications.
• Strong Python programming skills.
• Proven hands‑on delivery across system design, application development, testing, and operational stability.
• Proficiency in automation, CI/CD, and all aspects of the SDLC.
• Experience with pipelines and DAGs for data processing and/or machine learning.
• Demonstrated proficiency in cloud and AI/ML software practices.
• Strong problem‑solving, communication, and stakeholder collaboration skills.
• Familiarity with MLOps practices and tooling.
• Experience driving adoption of AI engineering tools (e.g., GitHub Copilot) for JIRA, documentation, coding, and releases, with measurable productivity and quality gains.

Preferred qualifications, capabilities, and skills

• Experience leading a small team as tech lead and/or manager.
• Proficiency with AWS (hands-on): Sage Maker, Bedrock, Glue, Redshift Serverless, DynamoDB, Event Bridge, Step Functions, Lambda, ECS, EKS, Kinesis, CloudWatch
• Experience with Python, Terraform, GitHub Copilot, Airflow, Kubernetes, Docker, MLflow, Datadog, Dynatrace, MCP.
• Familiarity with JPMC platforms/tools (highly preferred): Jules/JET, GKP (Gaia Kubernetes), Fusion MLOps