Lead Software Engineer, Data Platform

JPMorgan Chase

Quick summary

Work type
On-site
Location
Jersey City, NJ
Salary
$152,000–$215,000 / yr
Posted
16 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $200k
This role $184k
$143k most similar roles pay here $234k

This role pays less than 72% of similar roles. Most pay $183,500–$216,000 — the shaded band above. At the midpoint, this role pays about $184k versus about $200k for comparable roles.

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 436 open roles on FindRole.

Listed pay typically runs $152,000–$215,000 across 230 roles with salary data.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Lead Software Engineer, Data Platform

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Banking Data Analytics Payments Technology team, you will lead an agile squad tasked with developing and maintaining scalable data pipelines and ETL/ELT workflows for both batch and real-time processing using technologies like Spark, Airflow, Kafka, and Flink. Your daily tasks include designing data platform components such as cataloging systems, quality frameworks, and semantic layers while ensuring compliance standards are met. You will collaborate closely with analytics teams to implement robust data modeling strategies that support advanced reporting and analytics needs. The ideal candidate has extensive experience in software engineering or data platform development, proficiency in Python, Java, and SQL, and hands-on expertise with distributed data processing frameworks and cloud services like AWS S3, Glue, Redshift, and EMR. Additionally, familiarity with Kubernetes, Terraform, Docker, and semantic layer tools such as dbt Metrics is essential for this role that operates at a large scale within one of the world’s leading financial institutions.

What you'll do

  • Designs and builds scalable data pipelines using Spark, Airflow, Kafka, and Flink.
  • Develops data platform components including data cataloging and quality frameworks with governance standards.
  • Implements data modeling strategies to support analytics, reporting, and downstream consumption.
  • Partners with teams to translate data requirements into production-grade solutions.
  • Proficient in cloud data services like AWS S3, Glue, Redshift, Athena, EMR, Lake Formation.

What we're looking for

  • Demonstrated professional experience in software engineering or data platform development.
  • Proficient in Python, Java, SQL, Apache Spark, and Flink for distributed data processing.
  • Expertise in data modeling techniques including star schema, snowflake models, and query optimization.
  • Experience designing and operating data pipelines on Databricks with Apache Airflow orchestration.
  • Proficiency with cloud data services such as AWS S3, Glue, Redshift, Athena, EMR, Lake Formation.
  • Hands-on experience with Kubernetes for production-grade data platforms and open catalog integration.

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