Lead Software Engineer, Data Platform

JPMorgan Chase

Confirmed live today Trusted

Quick summary

Work type
On-site
Location
Jersey City, NJ
Employment
Full-time
Posted
28 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $175k
$108k $248k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $148,375–$201,600.

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 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Data Platform

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Lead Software Engineer - Data Platform joins the Commercial & Investment Banking – Data Analytics – Payments Technology team to build and deliver trusted, scalable technology products. This role involves designing, building, and maintaining scalable data pipelines for batch and real-time processing, as well as leading the evolution of event-driven microservices workflows. You will implement data modeling strategies like fact and dimensional tables to support analytics and reporting. Key responsibilities include driving team adoption of AI-assisted engineering practices, managing enterprise applications, and ensuring production readiness through observability. Required technical skills include proficiency in Python, Java, and SQL, along with hands-on experience using Spark, Flink, Kafka, and Airflow. You must also demonstrate expertise in AWS cloud services, including S3, Glue, Redshift, and Athena, while applying agile methodologies like CI/CD.

Skills

Python Java SQL Apache Spark Flink Kafka Apache Airflow Spring Boot AWS Databricks Redshift Glue Athena EMR Lake Formation S3 CI/CD Data Modeling Microservices

What you'll do

  • Design, build, and maintain scalable data pipelines for batch and real-time processing using Spark, Airflow, Kafka, and Flink.
  • Lead the design and evolution of event-driven microservices workflows using Kafka for reliable asynchronous processing.
  • Implement data modeling strategies, including fact and dimensional tables, to support analytics and reporting.
  • Set and uphold engineering standards for Spring Boot services, including API design, security, and performance tuning.
  • Develop secure production code and conduct code reviews and debugging for other team members.
  • Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
  • Ensure production readiness through observability, metrics, tracing, alerting, and proactive incident response.
  • Translate business requirements from stakeholders into production-grade software solutions.

What we're looking for

  • Formal training or certification on software engineering concepts and 5+ years of applied experience.
  • Demonstrated professional experience focused on software engineering or data platform development.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability.
  • Advanced proficiency in one or more programming languages, specifically Python, Java, and SQL.
  • Hands-on experience with distributed data processing frameworks such as Apache Spark and Flink.
  • Proficiency with cloud data services including AWS S3, Glue, Redshift, Athena, EMR, Lake Formation, or equivalent.
  • Advanced understanding of agile methodologies, CI/CD, application resiliency, and security.
  • Experience designing and operating data pipelines on Databricks using Apache Airflow (preferred).

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