Experience : 8–10 years overall, with 3+ years of Azure experience. Required Skills Strong hands-on experience with Azure Data Factory (ADF) — pipelines, data flows, triggers, integration runtimes, parameterization, erro…
Engineering & IT · Houston, TX
Data Engineer jobs in Houston, TX
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.
616
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$37–$92/hr
Typical pay range
$126k
Median, full-time
5
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Open data engineer roles
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Senior Data Engineer WhiteWater Express Car Wash — Houston, TX | Full-Time | On-Site| Location: 106 Vintage Park Blvd. Houston, TX 77070 Note: Position is not eligible for visa sponsorship. Must live within Houston, TX a…
$80 per hour
Job Description Job Description Job Description: Design, develop, and maintain data pipelines and infrastructure to collect, process, and analyze large datasets. Implement ETL processes, optimize database performance, an…
NAVA Software is looking for a Lead Data Engineer Details: Lead Data Engineer Location: Houston TX Monday to Thursday onsite Duration: 6-12 months Position Overview The Lead Data Engineer is responsible for defining, imp…
Job Description Job Description Quanex is looking for a Sr. Data Engineer to join our team located in Houston, Texas. The Sr. Data Engineer is responsible for designing, building, and maintaining scalable data pipelines…
ADF Data Engineer Houston, TX, 77079 Hire Type: Contract Experience: 5 8 years in data engineering with at least 3+ years on Azure. Azure Data Factory: Pipelines, data flows (mapping/wrangling), triggers, integration run…
Join the ECI Group's Professional Technical Services Network as a contract Sr Data Engineer . This is a Houston based contract role with an anticipated 4-month duration with an estimated start date of August 24th. Note:…
industry and delivering exceptional customer experiences, join our team today. Position Specific Description As a Senior Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipel…
position is based in Houston, Texas office; candidates in Houston and the surrounding area are required. Welcome to Love's! The Data Engineer III designs, builds, and supports scalable data solutions that advance Love’s…
Rysun Labs (formerly KCS – Krish Compusoft Services) is an AI, Data & Digital innovation partner of choice for enterprises. Rysun guides... ...Contributor). We are seeking a skilled and motivated Data Engineer to design,…
Foxconn Houston has several Lighthouse Factory plants manufacturing servers and server cabinets. The company is hiring dedicated data engineers to ensure its data is accessible, secure, and efficient. This role collabora…
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What data engineers earn in Houston
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 Houston 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
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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
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Junior Data Engineer
02
Data Engineer
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Senior Data Engineer
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Staff Data Engineer
05
Data Platform Lead
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