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Engineering & IT · Raleigh, NC
Data Engineer jobs in Raleigh, NC
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.
201
Open roles today
$37–$93/hr
Typical pay range
$128k
Median, full-time
7
Fresh in this list
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01
Open data engineer roles
12 shown of 201 · sorted by freshness
$104.9k - $174.7k
Salary: $104,900 - 174,700 per year Requirements: We are looking for someone with 10+ years of engineering experience, along with experience in data strategy and data management. A bachelors degree is preferred in Engine…
$94.69k - $122.54k
developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description AI/ML Data Engineering Specialist, US Commercial As part of our enterprise AI strategy to speed life-ch…
you to grow and excel.Job DescriptionIn the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as... ...agentic workflows (tool calling, memory, multi-agent), and prompt engineering. • Wo…
designing solutions for both functional and non-functional requirements• High level of competency in software design and software engineering implementation.• Well Versed with common design patterns• XML Webservices expe…
Job-ID29195954Reference26-24664Remote100% Remote o Conduct data profiling and quality assessments across source systems to identify gaps, duplicates, and inconsistencies in party records, translating findings into priori…
enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply... ...AI solutions across the full technology stack: identity, data, security,…
Job Summary (List Format): - Serve as a Data Engineer focused on quality assurance, quality checking, and ETL processes - Ensure accuracy and integrity of data transferred from shared file transfer services to S3 buckets…
Job Summary (List Format): - Serve as Data Engineer for DHHS-ITD, focusing on the design, development, and optimization of cloud-based analytics environments. - Build and maintain scalable ETL/ELT data pipelines using Az…
$77.8k - $136.2k
Data Engineer Position Description CGI is seeking an experienced Data Engineer with a strong database development background to design, develop, and modernize enterprise data solutions. The ideal candidate will bring exp…
$77.8k - $172.4k
Sr. Data Engineer Position Description CGI is seeking an experienced Senior Data Engineer with a strong database development background to design, develop, and modernize enterprise data solutions. The ideal candidate wil…
$92k - $130k
JOB DESCRIPTION SUMMARY Greystar's D²AI organization ( Data, Digital, and AI) is responsible for the platforms, processes,... ...tools in your day-to-day work, and partnering effectively with engineering, analytics, and…
02
What data engineers earn in Raleigh
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 Raleigh 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.
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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.
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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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