Senior Data Engineer — ETL Pipelines, Python & Cloud

JPMorganChase; Columbus (OH); On-site; USD 120,000 - 150,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a seasoned data engineer to design, build, and optimize large-scale ETL pipelines in a cloud-first environment.

You will develop Python applications, leverage PySpark, and ensure high-quality, scalable data solutions for critical business insights. You will work with cutting-edge technologies such as Iceberg/Delta Lake, Snowflake, and AWS services, and participate in code reviews, testing, and CI/CD adoption.

Qualifications

• 5+ years of data engineering experience in a corporate environment.
• Proficiency in Python, PySpark, SQL and ETL development.
• Experience with distributed data processing and data lake architectures.

Responsibilities

• Design and optimize large-scale ETL data pipelines.
• Develop Python applications with modular code and tests.
• Build distributed data processing with PySpark.
• Implement orchestration with Airflow/MWAA and Control-M.
• Develop cloud-native solutions on AWS (Glue, Athena, Lambda).
• Manage data lake architectures with Iceberg/Delta Lake.
• Administer Snowflake environments and security.
• Lead code reviews and promote CI/CD practices.

Skills

Python

PySpark

SQL

Airflow

MWAA

AWS

DBT

Snowflake

Education

Bachelor's degree in Computer Science or related field

Master's degree in Data Engineering or related field

Tools

Control-M

Iceberg

Delta Lake

Glue

Terraform

Git

CI/CD

Job description

JPMorgan Chase & Co. is seeking a seasoned data engineer to design, build, and optimize large-scale ETL pipelines in a cloud-first environment.

You will develop Python applications, leverage PySpark, and ensure high-quality, scalable data solutions for critical business insights. You will work with cutting-edge technologies such as Iceberg/Delta Lake, Snowflake, and AWS services, and participate in code reviews, testing, and CI/CD adoption.