JPMorgan Chase
Lead Data Engineer - ETL Java AI
Columbus, OH · Full-time · Posted Oct 15, 2026
- Experience
- 5+ years of applied experience in software engineering concepts; 10+ years of software engineering experience.
- Education
- Formal training or certification on software engineering concepts.
About the job
Leads architecture and hands-on delivery of large-scale data pipelines and Java services, while guiding secure, validated use of AI-assisted engineering practices.
What you'll do
- Designs, builds, and operates ETL/ELT pipelines, data lake patterns, and distributed processing workloads.
- Develops Java services, REST APIs, and integration components for data workflows and downstream consumption.
- Leads adoption of AI-assisted engineering practices, setting validation standards for code quality, security, and performance.
What they ask for
- Formal training or certification in software engineering concepts and 5+ years of applied experience.
- 10+ years of software engineering experience, with strong depth in data engineering/big data platforms.
- Strong hands-on Java development and proficiency in at least one data-focused language such as Python.
- Experience building ETL/ELT pipelines and with Apache Spark, data formats such as Parquet and Avro, data lake/lakehouse patterns, and Snowflake or an equivalent cloud data warehouse.
Nice to have
- Experience with orchestration tools, streaming/event-driven processing, or table formats such as Delta Lake, Apache Iceberg, or Hudi.
- Experience with Agentic AI / Gen AI solutions and capabilities.
Tools
Java, Python, Apache Spark, Parquet, Avro, Snowflake, Airflow, Dagster
AI focus
Leads team adoption of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting; sets standards for validating outputs and responsible, secure use. Experience with Agentic AI / Gen AI is an added advantage.
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