Overview Summit Human Capital is seeking a 100% Remote Senior Data Engineer to join a fully virtual team. In this role, you’ll design and build scalable data solutions for a leading financial client, collaborating with s…
Data Engineer jobs in Richmond, VA
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.
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Open data engineer roles
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application running on Mod PLSQL gateway. This technology is outdated. All the modules in client capture and deal with highly sensitive data (PII and PHI), so web application security is a high priority aspect for the cl…
Job Description Job Description Data EngineerRichmond, VA 23219 (hybrid) Pay: $100,000-120,000 Role Summary The Senior Data Engineer is a hands-on expert and technical leader, actively engaged in designing, building, and…
Job Description Job Description Sr. Data Analytics Engineer 10874 A growing organization is seeking a Senior Analytics Engineer to lead the modernization of its enterprise data platform. This individual will evaluate, de…
Overview Lead Data Engineer - Data Publication and Transformation Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and…
government agencies, a list that spans across the country. Job Description CapTech Machine Learning Engineers are responsible for designing and implementing data- driven solutions for our clients, with a specific focus o…
companies, mid-sized enterprises, and government agencies, a list that spans across the country. Job Description CapTech Data Engineering consultants enable clients to build and maintain advanced data systems that bring…
, mid-sized enterprises, and government agencies, a list that spans across the country. Job Description CapTech Data Engineering consultants enable clients to build and maintain advanced data systems that bring together…
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…
Overview Lead Data Engineer - Data Transformation (Modeling and Architecture) Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, in…
Job Description Job Description ~ This position is hybrid in Richmond, VA. Our client has an opening for a Oracle APEX Developer / Programmer Analyst 3 (796854) This position is up to 15 months with the option of extensi…
Richmond, VA (Hybrid) Duration: Through July 31, 2026 with possible extension Role Summary: Seeking a Database Administrator / Data Engineer with experience migrating on-prem SQL Server databases to AWS and Snowflake. Th…
What data engineers earn in Richmond
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $37–$51 | $77k–$107k |
| Mid level | $51–$71 | $107k–$148k |
| Senior | $69–$93 | $144k–$193k |
Adjusted for the Richmond market from national ranges.
What employers ask for
The skills these listings keep naming
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.
Resume tips that move the needle
For data engineers specifically — generic advice costs you here
State data scale plainly — rows per day, terabytes managed, pipeline counts — because it is the first thing hiring managers scan for.
Name your orchestration, processing, and warehouse tools per role; the modern stack (Airflow, dbt, Snowflake) is a keyword screen.
Highlight reliability outcomes: pipeline failure rates, data freshness SLAs met, incident reductions.
Show cost work if you have it — warehouse spend is a live concern and optimization stories differentiate.
Mention who consumed your data (analysts, ML teams, executives) to show you build for users, not just movement.
Where this role goes
Typical progression
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