Lead Data Engineer - Cloud-Scale Data Pipelines

DataJobs; Chicago (IL); On-site; USD 133,000 - 175,000; Full time

Job summary

JPMorganChase in Chicago, IL is seeking a Lead Data Engineer to design, implement, and maintain data pipelines and secure data architectures for the Corporate Technology team. The role focuses on timeliness, data quality, and regulatory compliance, with end-to-end solution delivery and influence over technical strategy.

The candidate will work with Java, Python, SQL, Spark, Kafka and cloud services across GCP/AWS, ensuring robust data governance, observability, and performance at scale.

Qualifications

• Experience designing, building and optimizing production ETL/ELT pipelines (batch and streaming).
• Strong Java and Python skills with testing and code review practices.
• Proficient SQL with joins, aggregations, subqueries, and window functions.

Responsibilities

• Design and develop scalable, secure distributed architectures for data ingestion and processing using cloud-native tech.
• Design, implement, and maintain data pipelines that collect, process, and store large data volumes with timeliness, quality and completeness.
• Ensure compliance with data residency and privacy regulations and apply security best practices for data in transit and at rest.

Skills

Java

Python

SQL

Spark

Flink

Dataflow

Kafka

schema registry

data modelling

partitioning

clustering

Snowflake

Databricks

cloud storage

Tools

Delta

Iceberg

Avro

Parquet

Job description

JPMorganChase in Chicago, IL is seeking a Lead Data Engineer to design, implement, and maintain data pipelines and secure data architectures for the Corporate Technology team. The role focuses on timeliness, data quality, and regulatory compliance, with end-to-end solution delivery and influence over technical strategy.

The candidate will work with Java, Python, SQL, Spark, Kafka and cloud services across GCP/AWS, ensuring robust data governance, observability, and performance at scale.