Lead Data Engineer: Architect Scalable Data Platforms

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

Job summary

JPMorgan Chase & Co. in Jersey City is seeking a Lead Data Engineer to drive data collection, storage, access, and analytics platforms across the enterprise.

You will be a core technical contributor, delivering secure, scalable data pipelines and architectures that support multiple business functions. The role emphasizes hands-on data engineering with Python, PySpark, SQL, and Airflow, mentoring juniors, and collaborating with analysts and data scientists to turn requirements into robust data

Qualifications

• Formal training or certification on data engineering concepts and 5+ years applied experience
• Demonstrated experience delivering in an agile, fast-paced engineering environment. Hands-on professional experience actively coding as a data engineer
• Strong software engineering fundamentals (system design, data structures, object-oriented programming, testing strategies, and end-to-end development lifecycle)
• Strong understanding of creating and maintaining data models (conceptual, logical, and physical), including dimensional and normalized modeling approaches
• Hands-on experience building and operating cloud-based data platforms using major cloud services (e.g., AWS, Google Cloud, or Azure)
• Experience with large-scale distributed data processing and performance tuning
• Hands-on experience with modern data warehousing/lakehouse technologies. Strong SQL skills and experience with SQL-based transformation tooling
• Experience designing and operating orchestration pipelines using Airflow or similar tools
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity
• Ability to review and validate AI-assisted outputs (e.g., model/design summaries or operational checklists) before use, escalating when uncertain and following data handling requirements

Responsibilities

• Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
• Build and optimize batch and streaming data pipelines with strong performance, fault tolerance, and observability
• Develop and operate workflow orchestration (e.g., Apache Airflow) to schedule, monitor, and manage data movement and transformations
• Model and transform data for analytics using SQL to support business intelligence and reporting workloads
• Write production-grade Python/PySpark code with disciplined testing, performance tuning, and maintainable object-oriented design
• Collaborate with analysts, data scientists, and application teams to turn requirements into technical designs and delivered solutions
• Own critical data systems by improving reliability, scalability, security, and operational excellence
• Mentor junior engineers and influence the team’s technical direction through standards, reviews, and knowledge sharing
• Uses enterprise AI capabilities to accelerate data platform and model design analysis, with validation and secure data handling
• Applies reuse-first, AI-assisted practices to delivery and operations, ensuring traceability and security alignment

Skills

Data engineering

Agile

Software fundamentals

Data modeling

Cloud platforms

Distributed processing

Data warehousing

Airflow

AI capabilities

Tools

Apache Airflow

SQL

Python

PySpark

Cloud services

Job description

JPMorgan Chase & Co. in Jersey City is seeking a Lead Data Engineer to drive data collection, storage, access, and analytics platforms across the enterprise.

You will be a core technical contributor, delivering secure, scalable data pipelines and architectures that support multiple business functions. The role emphasizes hands-on data engineering with Python, PySpark, SQL, and Airflow, mentoring juniors, and collaborating with analysts and data scientists to turn requirements into robust data