Lead Data Engineer: Build Scalable Pipelines & AI-Driven Data

Next Frontier Capital; Jersey City (NJ); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health benefits

On-site wellness centers

Retirement savings plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching

Job summary

JPMorganChase is seeking a Lead Data Engineer to join a fast-paced agile team focused on building secure, scalable data platforms. You will own data pipelines, implement batch and streaming workflows, and collaborate across analysts, data scientists, and applications teams to turn requirements into robust designs.

You will contribute by writing Python/PySpark, optimizing performance, and mentoring engineers while upholding strict security and data-sensitivity standards.

Qualifications

• Formal training or certification on data engineering concepts and 5+ years applied experience.
• Hands-on coding as a data engineer in an agile, fast-paced environment.
• Strong fundamentals in system design, data structures, testing, and end-to-end lifecycle.
• Experience with data models (dimensional/normalized) and SQL-based transformations.

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-authorized AI capabilities within the work environment to accelerate data platform and model design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Applies reuse-first, AI-assisted practices within delivery and operational routines, ensuring traceability and alignment to resiliency and security expectations.

Skills

Data pipelines

Airflow

PySpark

SQL

Cloud platforms

Data modeling

Python

Education

Data engineering certification

Tools

AWS

GCP

Azure

Apache Airflow

Job description

JPMorganChase is seeking a Lead Data Engineer to join a fast-paced agile team focused on building secure, scalable data platforms. You will own data pipelines, implement batch and streaming workflows, and collaborate across analysts, data scientists, and applications teams to turn requirements into robust designs.

You will contribute by writing Python/PySpark, optimizing performance, and mentoring engineers while upholding strict security and data-sensitivity standards.