Position Overview We are seeking an experienced Data Engineer III to design, develop, and maintain modern enterprise data platforms supporting business intelligence and analytics initiatives. This role focuses on buildin…
Engineering & IT · Cincinnati, OH
Data Engineer jobs in Cincinnati, OH
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.
132
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$35–$87/hr
Typical pay range
$120k
Median, full-time
4
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Open data engineer roles
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by intelligent machines. If you're driven by ambition, success, fun, and learning, Nexaminds is where you belong. As a Data Testing Engineer , you will be the Quality subject-matter expert on a dedicated Scrum Team, ensu…
Description Job Description For more than three decades, Strategic Data Systems (SDS) has been a software consultancy firm specializing... ...of our dynamic and cohesive community. Job Title: Data Engineer II Location: C…
$55 - $70 per hour
Cincinnati, Ohio Duration: Contract Job ID: 178780 Job Overview: We are seeking a highly skilled and experienced Senior Data Engineer to design, develop, and support scalable IBM DataStage ETL solutions and enterprise da…
Our corporate activities are growing rapidly, and we are currently seeking a full-time, office-based Junior Data Engineer to join our Information Technology team. This position will work on a team to accomplish tasks and…
Greetings, We’re looking for a senior-level Data Engineer with expertise in DBT, Snowflake, and SQL to design and deliver scalable data solutions in a high-impact banking environment. Data Architect / Principal Data Engi…
Job Description Job Description ComResource is looking for a Data Platform Engineer. Responsibilities: Design and implement Dataiku Project Standards to act as a production readiness linter, ensuring all projects meet na…
Job Title: Data Engineer IV Location: Cincinnati, OH - onsite Payrate $70/hr on W2. USC and GC Holder candidates only. TOP SKILLS: Must Have Python SQL Nice To Have AWS Sagemaker DBT Snowflake What You'll Do Squad: Machi…
Job Description Job Description Description: On Site in Cincinnati, Ohio Our client seeks a Data Engineer/ Architect III to assess and optimize Cloudera NiFi implementations, strengthen ETL and ELT pipelines, and enable…
Job Description Job Description Sr. Data Engineer for Cincinnati OH Will work on the projects from inception to end using Azure cloud technologies like PySpark, Spark SQL, Azure Data Lake Storage, Azure Data Factory, Azu…
Description Job Description For more than three decades, Strategic Data Systems (SDS) has been a software consultancy firm specializing... ...of our dynamic and cohesive community. Job Title: Data Engineer - Datastage ET…
Job Description Job Description ComResource is looking for a Data Engineer. We need someone to assist in calculating FDIC insurance at the customer and bank levels using traditional and modern data engineering tools. Thi…
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What data engineers earn in Cincinnati
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $35–$48 | $73k–$100k |
| Mid level | $48–$67 | $100k–$140k |
| Senior | $65–$87 | $135k–$181k |
Adjusted for the Cincinnati 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
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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