JPMorgan Chase
Lead Software Engineer - Data Engineer
$157K–$215K
Jersey City, NJ · Full-time · Posted Jul 2, 2026
- Experience
- 5+ years of applied experience in software engineering concepts and 5+ years building production data engineering and/or software engineering solutions.
- Education
- Formal training or certification on software engineering concepts; equivalent experience is not stated.
About the job
Leads data engineering for regulatory reporting, building and operating secure, scalable Spark-based data pipelines and promoting AI-assisted engineering practices across the team.
What you'll do
- Designs, develops, troubleshoots, and maintains production data pipelines using Python/PySpark and Spark SQL.
- Improves pipeline reliability and lakehouse operations, including automation, performance tuning, and Apache Iceberg maintenance.
- Leads adoption of approved AI-assisted engineering practices, validates safe and reliable use, and guides technical evaluations and team learning.
What they ask for
- Formal training or certification in software engineering concepts and 5+ years of applied experience; also requires 5+ years building production data engineering and/or software engineering solutions.
- Advanced Python proficiency and strong hands-on PySpark experience; advanced Spark SQL proficiency and strong SQL fundamentals.
- Production experience delivering and operating Spark workloads on EMR and/or Databricks, and production Apache Iceberg expertise.
- Experience with AWS data management patterns, including S3 and AWS Glue Data Catalog; proficiency in CI/CD, automated testing, and repeatable deployments. Also requires hands-on experience with large-scale data pipeline design, development, testing, and operations.
Nice to have
- Kafka familiarity; experience with Delta Lake or Spark Structured Streaming.
- Working knowledge of Java; experience with AI-assisted engineering tools such as GitHub Copilot or Claude.
Pay
USD 156,750.00-$215,000.00 base salary
Tools
Python, PySpark, Spark SQL, AWS, S3, AWS Glue Data Catalog, EMR, Databricks
AI focus
Leads enterprise-authorized AI-assisted engineering for coding, code review, refactoring, testing, troubleshooting, and incident analysis; sets validation standards and coaches on responsible, secure, compliant use.
Model-written summary · the original posting is authoritative