Job Details

Skills

• Lead Data Engineer

Summary

job summary:

Are you a Data Engineer with over 10 years of experience and expertise working with Databricks on AWS?

Overview:

We are investing in the next evolution of our data, analytics, and artificial intelligence ecosystem. We are looking for a Lead Data Engineer who's ready to do more than just build pipelines on Databricks and AWS.

You will help shape enterprise analytics strategy, influence architecture, and partner directly with the business to drive smarter decisions.

Why This Role?

This is a high-impact, high visibility role where you will:

Lead the design and implementation of a modern AWS + Databricks Lakehouse platform

Partner across IT, analytics, and business teams to turn data into decisions

Drive scalable, governed, high-performance data solutions

Influence how data powers analytics, reporting, and AI across the company

Our transportation client is looking for a seasoned Data Engineer to lead the design and implementation of their modern AWS and Databricks Lakehouse platform.

You will design and lead enterprise-grade pipelines, own the ETL/ELT lifecycle, drive data engineering standards and architecture, and translate business requirements into scalable, high-performing solutions.

Apply if you are a good fit and local to the Chicagoland area, interviews will be onsite in Chicago.

location: Chicago, Illinois

job type: Contract

salary: $70 - 83 per hour

work hours: 9am to 5pm

education: Bachelors

responsibilities:

Why This Role?

This is a high-impact, high visibility role where you will:

Lead the design and implementation of a modern AWS + Databricks Lakehouse platform

Partner across IT, analytics, and business teams to turn data into decisions

Drive scalable, governed, high-performance data solutions

Influence how data powers analytics, reporting, and AI across the company

What You'll Be Doing

Design and lead enterprise-grade pipelines, supporting both batch and streaming data processing

Own the full ETL/ELT lifecycle, from design through production support

Drive data engineering standards, best practices, and architecture across the data ecosystem

• Translate business requirements into scalable, high-performance data solutions