Lead Software & Data Engineer: Spark, AI-Assisted Dev

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 150,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. in Jersey City invites a Lead Software Engineer to join the CIB Regulatory Reporting Team.

You will be a core technical contributor delivering secure, scalable data pipelines and production code in Python with PySpark and Spark SQL. You will promote AI-assisted engineering practices, work with vendors and internal teams on EMR/Databricks and Iceberg lakehouse designs, and help ensure reliability, governance, and performance across critical datasets.

Qualifications

• 5+ years of professional software or data engineering experience.
• Strong Python and PySpark experience with Spark SQL.
• Experience delivering production data pipelines and data lakehouse concepts.

Responsibilities

• Executes creative software solutions with data engineering and ETL/ELT focus.
• Develops production Python/PySpark code and reviews Spark jobs.
• Drives AI-assisted engineering practices to improve code quality and delivery speed.
• Applies SDLC tools to improve automation and deployment.
• Identifies opportunities to automate recurring issues for stability.
• Leads evaluation sessions with vendors and internal teams on architecture.
• Leads communities of practice around Spark performance and data platforms.
• Adds to team culture of diversity, inclusion, and respect.

Skills

Python

PySpark

Spark SQL

Data engineering

SQL

Leadership

Cloud AWS

AI-assisted tools

Education

Formal software engineering training

Tools

Spark

EMR/Databricks

AWS Glue Data Catalog

S3

Iceberg

CI/CD

Python IDEs

Job description

JPMorgan Chase & Co. in Jersey City invites a Lead Software Engineer to join the CIB Regulatory Reporting Team.

You will be a core technical contributor delivering secure, scalable data pipelines and production code in Python with PySpark and Spark SQL. You will promote AI-assisted engineering practices, work with vendors and internal teams on EMR/Databricks and Iceberg lakehouse designs, and help ensure reliability, governance, and performance across critical datasets.