Lead Software Engineer, Data Engineer

JPMorgan Chase

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: Jersey City, NJ
Posted: 71 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $201k

$174k most similar roles pay here $231k

This listing doesn't post a salary. Most similar roles pay $190,137–$211,200.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Lead Software Engineer, Data Engineer

Role Posting Log in to save

As a Lead Software Engineer - Data Engineer within the Commercial & Investment Bank Regulatory Reporting Team, you will join an agile team to build and deliver secure, scalable technology products. You will serve as a core technical contributor responsible for designing, developing, and troubleshooting complex software solutions with a focus on Spark-based ETL/ELT processes. Your daily work involves writing production code in Python, PySpark, and Spark SQL while leading the adoption of AI-assisted engineering practices to improve code quality and delivery speed. You will manage large-scale data pipelines, maintain lakehouse architectures using Apache Iceberg, and operate workloads on EMR or Databricks. Key technical requirements include expertise in AWS S3, Glue Data Catalog, CI/CD automation, and SQL optimization. You will also lead communities of practice regarding Spark performance and data platform operations.

Skills

Python PySpark Spark SQL Spark Apache Iceberg Databricks AWS EMR S3 SQL CI CD Data Engineering ETL Kafka Delta Lake Java GitHub Copilot Claude

What you'll do

Develop high-quality production code in Python, PySpark, and Spark SQL for data engineering tasks.
Design and troubleshoot complex technical solutions focusing on Spark-based ETL/ELT processes.
Drive the adoption of AI-assisted engineering practices to improve code quality and delivery speed.
Automate the remediation of recurring issues to improve data pipeline reliability and system stability.
Lead evaluation sessions with vendors and internal teams to assess architectural designs and technical credentials.
Lead communities of practice to promote best practices in Spark performance and Iceberg table management.
Manage large-scale data pipelines using cloud platforms like EMR or Databricks.
Implement CI/CD methods and automated testing for reliable data pipeline deployments.

What we're looking for

Formal training or certification in software engineering concepts.
5+ years of experience in software engineering or production data engineering solutions.
Advanced proficiency in Python and PySpark for developing high-quality production code.
Advanced proficiency in Spark SQL with strong fundamentals in data modeling and query optimization.
Experience delivering system design, testing, and operational stability for large-scale data pipelines.
Expertise in Apache Iceberg table design, maintenance, and performance optimization.
Experience operating Spark workloads on EMR or Databricks platforms.
Proficiency in CI/CD methods, automated testing, and automation of data pipeline deployments.

Save