Engineering & IT · Richmond, VA

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.

158
Open roles today
$37–$93/hr
Typical pay range
$128k
Median, full-time
2
Fresh in this list

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01

Open data engineer roles

12 shown of 158 · sorted by freshness

100% Remote Senior Data Engineer

Summit Human Capital · Richmond, VA · Full-time
$135k - $170k

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…

Posted yesterday
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Data Engineer

CEI · Richmond, VA
$100k - $120k

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…

Posted 1w ago
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Sr. Data Analytics Engineer

Thomas Edwards Group · Midlothian, VA

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…

Posted 1w ago
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Machine Learning / Data Science Engineer

CapTech Consulting · Richmond, VA
$90k - $200k

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…

Posted 1mo ago
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Data Engineer (AWS, Azure, GCP)

CapTech Consulting · Richmond, VA
$90k - $200k

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…

Posted 1mo ago
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Senior Data Engineer (AWS, Azure, GCP)

CapTech Consulting · Richmond, VA
$90k - $200k

, 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…

Posted 1mo ago
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Lead Data Engineer

Capital One · Richmond, VA
$197.3k - $225.1k

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…

Posted 2mo ago
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Data base Administrator / Data Engineer

Career Land Center, LLC · Richmond, VA · Temporary

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…

Posted 5mo ago
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02

What data engineers earn in Richmond

Hourly first — that's how the offer arrives

ExperienceHourlyAnnual, 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.

03

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.

05

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.

02

Name your orchestration, processing, and warehouse tools per role; the modern stack (Airflow, dbt, Snowflake) is a keyword screen.

03

Highlight reliability outcomes: pipeline failure rates, data freshness SLAs met, incident reductions.

04

Show cost work if you have it — warehouse spend is a live concern and optimization stories differentiate.

05

Mention who consumed your data (analysts, ML teams, executives) to show you build for users, not just movement.

06

Where this role goes

Typical progression

01 Junior Data Engineer
02 Data Engineer
03 Senior Data Engineer
04 Staff Data Engineer
05 Data Platform Lead
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