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Engineering & IT · Louisville, KY
Data Engineer jobs in Louisville, KY
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.
30
Open roles today
$34–$85/hr
Typical pay range
$117k
Median, full-time
10
Fresh in this list
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01
Open data engineer roles
12 shown of 30 · sorted by freshness
We are looking for a Desktop Support Analyst to deliver hands-on technical assistance at a manufacturing site in Louisville, Kentucky. This contract opportunity with potential for a permanent role is ideal for someone wh…
Job ID: R235496Posted: 2026-09-14Location: Firstside Center Bldg (PA373); PNC Tower - Louisville (KY012)Type: Full timeCountry: United States of AmericaCompany: PNCPosition OverviewAt PNC, our people are our greatest dif…
$82.6k - $162.8k
in Computer Science, Information Technology, Risk Management, Engineering, or a similar fieldProfessional certifications such as Certified... ...solutions, security information and event management platforms, or data los…
CompanyBrightSpring Health ServicesOverviewThe Human Resources Information Systems Analyst is responsible for supporting operational data needs in our HR applications including ADP Enterprise, Cornerstone, iCIMS and any…
ResponsibilitiesThe Senior Clinical Applications Systems Analyst Epic independently defines system objectives, requirements, scope, and impact based on needs of clinical operations. Develops or modifies clinical informat…
$129.3k - $177.8k
Become a part of our caring communityThe Lead AI Automation Engineer will provide hands-on technical leadership for the design, engineering, and productionization of AI-enabled automation across the Data Governance organ…
$118.7k - $243.7k
sustainment of zero trust architectures to safeguard critical assets and data against emerging cyber threats.Serve as the subject matter... ...and Firewall Teams, Application Teams, Server Teams, Cloud Engineering Teams…
$106.9k - $147k
Become a part of our caring communityHumana is seeking a Senior Full Stack Software Engineer who will be responsible for building and enhancing the UI/UX layer of Humana's Enterprise Data Governance Platform and Control…
Job-ID27380861Reference26-03163Lead Data Scientist - Autonomous Goal ManagementJob Description SummaryThe Enterprise AI organization... ...-world environments. You’ll contribute to the scientific and engineering foundati…
Legacy Data Engineer Ab Initio / Netezza Location: Remote Job Type: Contract Job Overview We are seeking a Legacy Data Engineer with strong experience in ETL development and legacy data technologies. The ideal candidate…
Claude AI Data Engineer Location: Remote Job Type: Contract Job Overview We are seeking a Data Engineer with experience using Claude AI / Generative AI technologies to support data engineering, data processing, automatio…
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What data engineers earn in Louisville
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $34–$47 | $71k–$98k |
| Mid level | $47–$65 | $98k–$136k |
| Senior | $63–$85 | $132k–$177k |
Adjusted for the Louisville 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
04
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
01
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
01
Junior Data Engineer
02
Data Engineer
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Senior Data Engineer
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Staff Data Engineer
05
Data Platform Lead
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