Senior Data Engineering Lead: Cloud, AI & ETL Pipelines

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 150,000 - 210,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer – Data Engineering within the Consumer & Community Banking/Data Products team. You will lead an agile team to design trusted, scalable data products and secure software delivery.

Responsibilities include building ETL pipelines, PySpark processing, data lake design, Snowflake administration, and AI-assisted engineering practices to improve quality and delivery speed.

Qualifications

• 5+ years of data engineering experience in a corporate setting.

Responsibilities

• Design, develop, and optimize large-scale ETL data pipelines.
• Build Python applications with modular code, logging, and automated testing.
• Develop and maintain distributed data processing solutions using PySpark.
• Large scale end-to-end testing design and validation.
• Implement and support workflow orchestration using Control-M or Apache Airflow (MWAA).
• Develop cloud-native solutions leveraging AWS services, including Glue, Athena, Lambda, and CloudWatch.
• Design and manage modern data lake architectures utilizing Iceberg and/or Delta Lake.
• Administer and optimize Snowflake environments, including streams, tasks, roles, and warehouses.
• Participate in code reviews and champion engineering best practices, testing standards, and CI/CD processes.
• Leverage approved AI-assisted development tools while ensuring secure, responsible, and compliant software delivery.

Skills

Python

Java

PySpark

SQL

ETL design

CI/CD

AI-assisted engineering

Security/compliance

Iceberg/Delta Lake

Snowflake

Airflow

Control-M

AWS

Tools

DBT

Snowflake

Airflow

Control-M

AWS Glue

Athena

Lambda

CloudWatch

Iceberg

Delta Lake

Job description

JPMorgan Chase & Co. is seeking a Lead Software Engineer – Data Engineering within the Consumer & Community Banking/Data Products team. You will lead an agile team to design trusted, scalable data products and secure software delivery.

Responsibilities include building ETL pipelines, PySpark processing, data lake design, Snowflake administration, and AI-assisted engineering practices to improve quality and delivery speed.