Lead Data Engineer

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Jersey City, NJ
Posted
33 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

How this pay compares to similar roles

Similar $180k
$141k most similar roles pay here $222k

This listing doesn't post a salary. Most similar roles pay $149,106–$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.

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At a glance

TL;DR · Lead Data Engineer

As a Lead Data Engineer within the Corporate Sector, you will join an agile team focused on building and delivering secure, stable, and scalable data collection, storage, access, and analytics solutions. You will serve as a core technical contributor responsible for maintaining critical data pipelines and architectures across various business functions to support firm objectives. Your daily responsibilities include developing batch and streaming pipelines with high fault tolerance, managing workflow orchestration using Apache Airflow, and modeling data for business intelligence via SQL. You will write production-grade Python and PySpark code while mentoring junior engineers and influencing technical direction. The role requires expertise in cloud-based platforms like AWS, Google Cloud, or Azure, along with experience in distributed data processing, modern lakehouse technologies, and utilizing enterprise-authorized AI capabilities to accelerate platform design and documentation.

What you'll do

  • Deliver secure, stable, and scalable data collection, storage, and analytics platform solutions.
  • Build and optimize high-performance batch and streaming data pipelines with fault tolerance and observability.
  • Develop and operate workflow orchestration systems like Apache Airflow to manage data movement and transformations.
  • Model and transform data using SQL to support business intelligence and reporting workloads.
  • Write production-grade Python and PySpark code with disciplined testing and object-oriented design.
  • Own critical data systems by improving reliability, scalability, security, and operational excellence.
  • Mentor junior engineers and influence technical direction through standards and peer reviews.
  • Utilize enterprise-authorized AI capabilities to accelerate platform design while ensuring data security compliance.

What we're looking for

  • Formal training or certification on data engineering concepts and 5+ years of applied experience.
  • Hands-on professional experience actively coding as a data engineer in an agile environment.
  • Strong software engineering fundamentals including system design, data structures, object-oriented programming, and testing strategies.
  • Experience building and operating cloud-based data platforms using major services like AWS, Google Cloud, or Azure.
  • Experience with large-scale distributed data processing and performance tuning.
  • Proficiency in modern data warehousing/lakehouse technologies and strong SQL skills for transformation tooling.
  • Experience designing and operating orchestration pipelines using Apache Airflow or similar tools.
  • Demonstrated experience using enterprise-authorized AI capabilities to support workflows while ensuring data sensitivity and validation.

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