JPMorgan Chase
Lead Software Engineer - Data Engineering | Data Technology
Columbus, OH · Full-time · Posted Sep 23, 2026
- Experience
- 5+ years applied experience with a strong focus on data engineering.
- Education
- Formal training or certification on software engineering concepts.
About the job
Leads engineering of scalable data pipelines and cloud-based data solutions for JPMorgan Chase’s Consumer & Community Banking Data Products team, while guiding engineering practices and responsible use of AI-assisted tools.
What you'll do
- Design, develop, test, and optimize ETL pipelines and distributed data processing solutions.
- Build and maintain cloud data platforms, orchestration workflows, data lakes, and Snowflake environments.
- Promote code quality, CI/CD, testing, and secure, responsible use of approved AI-assisted engineering tools.
What they ask for
- Formal training or certification in software engineering concepts.
- 5+ years of applied experience with a strong focus on data engineering.
- Experience with Python (primary) and/or Java (secondary), distributed data processing, DBT, and modern ETL practices.
- Experience with AWS data services, workflow orchestration, Iceberg and/or Delta Lake, Snowflake, and SQL.
Nice to have
- Experience with Kafka, Flink, or other streaming technologies; familiarity with AI/ML technologies including LLMs, prompt engineering, vector search, and responsible AI practices.
- Experience using AI-assisted development tools such as GitHub Copilot or Claude; financial services experience, mentoring, or technical delivery leadership.
Tools
Python, Java, PySpark, DBT (Data Build Tool), Control-M, Apache Airflow (MWAA), AWS Glue, Snowflake
AI focus
Drives adoption of enterprise-authorized AI-assisted engineering for code review and refactoring, test acceleration, and incident/root-cause analysis, with secure coding, peer review, and automated validation. Familiarity with AI/ML, LLMs, prompt engineering, vector search, responsible AI, and tools such as GitHub Copilot or Claude is preferred.
Model-written summary · the original posting is authoritative