$145k - $165k
in your work as we create a better future together.OverviewAs a Lead of Analytics Engineering at Avison Young Technologies, you will lead the strategy and execution of our proprietary data products and models that empowe…
Engineering & IT · Charlotte, NC
Data Engineer jobs in Charlotte, 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.
295
Open roles today
$37–$92/hr
Typical pay range
$126k
Median, full-time
8
Fresh in this list
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01
Open data engineer roles
11 shown of 295 · sorted by freshness
Job-ID29338960Reference26-26570The ideal candidate | Engineering- focused professional with a passion for automation, AI, and operational excellence... ...• Familiarity with AI governance, explainability, and trusted dat…
contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Database Engineering. Review and analyze complex multi-faceted, larger scale or longer-term Database…
contingent resource assignment, you may: Consult on or participate in moderately complex initiatives and deliverables within Software Engineering and contribute to large-scale planning related to Software Engineering del…
$201.5k - $302.5k
AVP, Platform Engineer - IPB05AEWe’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages... ..., too. Join our team as we help shape the future. As the AVP, Data Plat…
$156k - $234k
Dir Data Engineering - GE06AEWe’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals…
Managing Director, Data Engineering & AIWho You'll Work WithAs a Managing Director in Slalom's Data & AI practice, you will lead the growth of our Data Engineering & AI business by helping clients modernize their data fo…
$130k - $200k
The Red Ventures Home Client Services group is looking for a Data Engineering Manager to lead a team of up to four data engineers building the data platform that powers our home services business. In this role, you'll tr…
Data Engineer Location: Charlotte, NC Local Remote Duration: 6 Months Visa : USC/GC-EAD/H4-EAD Interview: 1st Round Virtual | 2nd Round In-Person Note: Must have recent financial client/financial services experience . Lo…
Data Engineer All IT Solutions United States · Charlotte, North Carolina Workplace Type — Remote Employment Type — Contract We are currently seeking a qualified Data Engineer to support this engagement. Please review the…
Must Have Skills Strong experience in AWS services (hands-on experience) Data engineering skills (Glue, ECS, Data pipeline etc,) primarily serverless, databases, storage services, container services, schedulers, and batc…
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What data engineers earn in Charlotte
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $37–$51 | $76k–$106k |
| Mid level | $51–$71 | $106k–$147k |
| Senior | $68–$92 | $142k–$191k |
Adjusted for the Charlotte 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
01
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
04
Staff Data Engineer
05
Data Platform Lead
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