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Engineering & IT · Memphis, TN
Data Engineer jobs in Memphis, TN
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.
29
Open roles today
$33–$83/hr
Typical pay range
$114k
Median, full-time
8
Fresh in this list
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01
Open data engineer roles
10 shown of 29 · sorted by freshness
$105.4k - $207.8k
in Computer Science, Information Technology, Risk Management, Engineering, or a similar fieldProfessional certifications such as Certified... ...solutions, security information and event management platforms, or data los…
$97.73k - $162.88k
Req ID:382980NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be... ...organization, apply now.We are currently seeking a AWS ETL Data Engineer - REMOTE…
headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Position: Service Engineer AI Data Center Location: Memphis, TN, 38118 Duration: 5 Months Job Type: Temporary Assignm…
$118.7k - $243.7k
sustainment of zero trust architectures to safeguard critical assets and data against emerging cyber threats.Serve as the subject matter... ...and Firewall Teams, Application Teams, Server Teams, Cloud Engineering Teams…
$87.12k - $151.25k
Req ID:375782NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be... ...organization, apply now.We are currently seeking a Site Reliability Engineer- REM…
$171.6k - $338.3k
Recruiting for this role ends on 12/31/2026.The Team:Deloitte’s Cyber Engineering is a new team that is spearheading the buildout of... ...degree in computer science, Engineering, Information Technology, Data Science, Ap…
Data Architect
at a FedEx location several times per week. Summary The AI Engineer is responsible for designing, developing, deploying, and... ...quality code, build scalable AI systems, including AI Agents and data pipelines, and inte…
$125.84k - $238.16k
discoveries that improve outcomes for children with catastrophic diseases through innovation, collaboration, and scientific excellence. The Data Scientist, Clinical Machine Learning and Flow Cytometry, will play a critic…
02
What data engineers earn in Memphis
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $33–$46 | $69k–$95k |
| Mid level | $46–$63 | $95k–$132k |
| Senior | $62–$83 | $128k–$172k |
Adjusted for the Memphis 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.
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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
03
Senior Data Engineer
04
Staff Data Engineer
05
Data Platform Lead
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