Lead Data Engineer - Cloud ETL, Data Lakes & AI Tools

JP Morgan Chase; Columbus (OH); On-site; USD 130,000 - 180,000; Full time

Job summary

JPMorgan Chase is seeking a Lead Software Engineer - Data Engineering within the Consumer & Community Banking/Data Products team. You will design and deliver trusted, scalable data solutions across multiple business functions in a secure environment.

Responsibilities include building ETL pipelines with PySpark, developing Python applications with testing, and managing cloud-native data lake architectures on AWS.

Qualifications

• Formal training or certification on software engineering concepts.
• 5+ years of applied data engineering experience.
• Experience with Python and Java in a large corporate environment.
• Hands-on with distributed data processing (e.g., PySpark).
• Knowledge of modern ETL development practices and data warehousing.

Responsibilities

• Design, develop, and optimize large-scale ETL data pipelines.
• Build Python applications with modular code and testing.
• Develop distributed data processing using PySpark.
• Design end-to-end test strategies and validation.
• Implement workflow orchestration with Control-M or Airflow MWAA.

Skills

Python

Java

PySpark

SQL

CI/CD

AI-assisted development

Education

Software engineering certification

Tools

Airflow (MWAA)

Control-M

Snowflake

AWS Glue

AWS Athena

AWS Lambda

Iceberg/Delta Lake

DBT

Job description

JPMorgan Chase is seeking a Lead Software Engineer - Data Engineering within the Consumer & Community Banking/Data Products team. You will design and deliver trusted, scalable data solutions across multiple business functions in a secure environment.

Responsibilities include building ETL pipelines with PySpark, developing Python applications with testing, and managing cloud-native data lake architectures on AWS.