$112k - $150k
Job Description Summary The Commercial Engine Services Business Intelligence (BI) team is building the next generation of analytics... ...supply chain and commercial operations. We're looking for a Staff Data Engineer to…
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.
90
Open roles today
$35–$87/hr
Typical pay range
$120k
Median, full-time
6
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01
Open data engineer roles
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manage, and optimize information and business processes. IT Services spans a wide range of activities, including software development, data management, Cloud services, IT security, technical support, access governance, i…
processes that run it. That work changes the operating model an engineering organization runs on, the ways of working underneath it, and... ...We combine our strength in technology and leadership in cloud, data and AI wi…
$110.7k - $218.3k
across personas such as Field Sales, KAM, MSLs, or Field Reimbursement ManagersExperience with adjacent Salesforce products such as Data Cloud, Experience Cloud, or MuleSoft based integrationsExperience delivering in a S…
$80.46k - $142.72k
is the world's leading company delivering sustainable design, engineering, and consultancy solutions for natural and built assets.We are... ...you will lead the electrical discipline of multiple concurrent data center pr…
Accenture's SAP Analytics practice, you will be a member of a delivery teams and focus on client engagements centered on SAP's modern data and analytics platform — including SAP Datasphere, SAP Analytics Cloud (SAC), and…
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…
$187.2k - $197.6k
Python, and Power BI. We are looking for hands-on experience building solutions in Microsoft Fabric or similar enterprise data engineering platforms. We require proven experience with ETL/ELT pipeline development, dimens…
convert business requirements into visual based analytics Conduct analysis for mapping source inputs and assist in design strategy for data modeling Daily maintenance support of dashboards Minimum Qualifications: Bachelo…
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…
$90 per hour
job summary: The Data Engineer - Finance Systems & Analytics plays a critical strategic role bridging the gap between Finance and Information Technology. In this position, you will transform complex business data require…
$140k - $180k
We are seeking an Azure AKS Architect with strong expertise in Azure, Kubernetes, Docker, DevOps, and Manufacturing Execution Systems (MES). The role will focus on designing, developing, deploying, and supporting scalabl…
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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
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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
05
Data Platform Lead
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