Data engineer • chicago il
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The average salary range is between $ 110,000 and $ 170,497 year , with the average salary hovering around $ 132,502 year .
The average salary range is between $ 105,570 and $ 172,017 year , with the average salary hovering around $ 130,000 year .
Lead Data Engineer
Chicago (ONSITE 1st month then remote)
LOCAL ONLY- Final round inv is onsite to meet the team ( 1st month is onsite then remote)
Job Description
***Looking for 10+ years of Data Engineering experience with the last 4+ years working with Databricks on AWS, NOT ON AZURE OR ANOTHER PLATFORM.***
Company:
Founded in 1898 and headquartered in Chicago, IL, GATX Corporation (NYSE: GATX) leases transportation assets and provides critical services to customers worldwide. Our diverse portfolio of assets includes railcars, locomotives, tank containers, and aircraft spare engines.
We are an industry leader with 125+ years of success - success that is powered by our people. We are proud of our high-performance culture, hard-working and enthusiastic management team, and beautiful office space in the Willis Tower.
Location: Chicagoland, IL candidates preferred, but work will be mostly remote with ability to come into Downtown office as needed.
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
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
Mentor a small team while remaining hands-on
Ensure data reliability, performance, governance, and cost optimization
Qualifications:
10+ years of IT experience, including deep expertise in data engineering & ETL
4-6+ years of recent hands-on experience in designing, building, and scaling data pipelines
Strong hands-on experience with Databricks (Spark, Delta Lake, Unity Catalog) and AWS (S3, IAM, networking)
Highly proficient in Databricks' core architectural pattern, which combines the best elements of data lakes and data warehouses.
Familiar with advanced features like Unity Catalog (for governance), Delta Live Tables (DLT for pipelines), Databricks SQL, and workflow orchestration.
Expertise in SQL, Python, data modeling, and distributed processing.
Experience with CI/CD, DevOps, and modern data architecture (lakehouse, medallion, etc.).
Experience working in an Agile analytics environment where close collaboration with key stakeholders to address evolving requirements is the norm.
Strong communication skills and the ability to translate complex technical concepts into solutions that deliver business outcomes.
A passion for continued learning and an interest in staying current with the rapidly evolving data and analytics space.
What Sets You Apart
You're analytical, curious, and solutions-oriented
You thrive in environments where you balance priorities and drive outcomes
You're comfortable with ambiguity and can quickly learn the business
You build strong partnerships and bring a "get things done" mindset
Interview Process:
60-90 minute technical interview with Director testing ability to do hands-on design work, to work in their database platform, etc. - IN PERSON IS IDEAL.
30-45 minute behavioral/team fit interview with Manager
Job Responsibilities
Are you a Data Engineer with over 10 years of experience and expertise working with Databricks on AWS?
Our trasnportation 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.
