$130k - $160k
W2 Only, No Sponsorship Available Full - Time $135,000 - $160,000/year Position Summary We're looking for a skilled Data Engineer to join our team. This role is responsible for the design and maintenance of various data…
Engineering & IT · Chicago, IL
Data Engineer jobs in Chicago, IL
Data engineers build the pipelines and warehouses that move data from source systems to the people and models that need it, keeping it fresh, correct, and queryable at scale.
682
Open roles today
$40–$101/hr
Typical pay range
$139k
Median, full-time
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Fresh in this list
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01
Open data engineer roles
12 shown of 682 · sorted by freshness
Description: Hybrid At least 2 days per week in office in Chicago, IL Our client seeks a Lead Data Engineer to design, build, and optimize large-scale data processing for attribution, measurement, forecasting, and privac…
$150k - $180k
sustainable, more inclusive world. Location Chicago IL Your Role We are seeking a highly experienced Foundry Lead Data Engineer to architect, develop, and optimize scalable data solutions using Palantir Foundry. This sen…
$100k - $150k
focused trading platform in the world. What you'll do: Your data- driven mindset and ability to work with large-scale data systems... ...new opportunities, and improve processes. As an accomplished data engineer joining…
focused on different domains - Customer, Loyalty, Search and Browse, Data Integration, Cart. Current overriding priorities are new... ...Demonstrated ability to lead cross-functional engineering teams, define technical s…
$100k - $115k
Management is an Equal Opportunity Employer (EOE). Position Summary: The Excel Analytics team is growing, and we are seeking a Data Engineer to help build and maintain the data pipelines and platforms that power our repo…
we're looking for people who can operate at the intersection of data, operations, and client experience. Position Overview... ...performant, resilient, and scalable. Key Responsibilities Data Engineering Design, build, a…
$106.5k - $182.6k
build-up and operationalization of an enterprise-class modern data environment, which may include various components within the Azure... ...Support existing data pipelines on-prem, cloud and business engineering extract…
$179.4k - $204.7k
Overview Lead Data Engineer, (Python, AWS) Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery env…
$179.4k - $204.7k
Overview Lead Data Engineer Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Ca…
Lead Data Engineer- Remote Remote (Chicago-area preferred) Visa: EAD/GC/Citizen only. 10+ years of IT experience, including deep expertise in data engineering & ETL; 4-6+ years of recent hands-on experience in designing,…
Job Summary We are looking for a skilled Data Engineer specializing in Graph Databases (Neo4j) to design and maintain robust data pipelines and model complex data structures. The ideal candidate will be responsible for c…
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What data engineers earn in Chicago
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $40–$56 | $84k–$117k |
| Mid level | $56–$78 | $117k–$162k |
| Senior | $75–$101 | $157k–$211k |
Adjusted for the Chicago market from national ranges.
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What employers ask for
The skills these listings keep naming
SQL and data modelingPython or ScalaAirflow or similar orchestrationSpark or other batch processingWarehouses (Snowflake, BigQuery)dbtStreaming (Kafka)Data quality testingCloud infrastructure
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Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Design a pipeline that loads data from a production database into a warehouse daily.
Cover extraction strategy, incremental loads versus full refresh, idempotency, and monitoring. Saying how you would backfill after a failure shows real pipeline experience.
How do you handle late-arriving or duplicate data?
Discuss idempotent upserts, watermarks, and dedup keys. This is a daily reality of the job, so a concrete example lands well.
Batch or streaming — how do you decide?
Anchor on the actual freshness requirement and cost. Most 'real-time' asks are fine at minutes; recognizing that is the mature answer.
A stakeholder says the numbers in their dashboard are wrong. Walk me through your debugging.
Trace lineage from the dashboard back to the source, isolating which layer diverged. Showing calm, structured lineage-tracing is the point of the question.
How do you model data for analytics — star schema, wide tables, something else?
Show you know the classic patterns and modern warehouse economics, and that you choose based on query patterns and team skill, not doctrine.
How do you test data pipelines?
Talk about schema and freshness checks, row-count and distribution tests, and tools like dbt tests or Great Expectations — plus alerting when they fail.
Tell me about a pipeline that failed badly and what you changed.
Structure it like an incident review: impact, cause, fix, prevention. Emphasize the durable improvement, such as monitoring or contract enforcement.
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Resume tips that move the needle
For data engineers specifically — generic advice costs you here
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State data scale plainly — rows per day, terabytes managed, pipeline counts — because it is the first thing hiring managers scan for.
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Name your orchestration, processing, and warehouse tools per role; the modern stack (Airflow, dbt, Snowflake) is a keyword screen.
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Highlight reliability outcomes: pipeline failure rates, data freshness SLAs met, incident reductions.
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Show cost work if you have it — warehouse spend is a live concern and optimization stories differentiate.
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Mention who consumed your data (analysts, ML teams, executives) to show you build for users, not just movement.
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Where this role goes
Typical progression
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Junior Data Engineer
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Data Engineer
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Senior Data Engineer
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Staff Data Engineer
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Data Platform Lead
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