only in your community, but around the world. We believe building engineering is more than systems and structures, it’s about powering... ...where people work, connect, and thrive. From high-performance data centers driv…
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.
418
Open roles today
$37–$92/hr
Typical pay range
$126k
Median, full-time
7
Fresh in this list
No email, no resume, no sign-up. Save any listing below and you start anonymously.
You're signed in. Saving a listing drops it straight into your pipeline.
01
Open data engineer roles
11 shown of 418 · sorted by freshness
Senior Data Engineer - Azure / DatabricksLocation: Houston, TX - HybridPosition Type: Full-TimeA well-established Houston-based company is seeking an experienced Senior Data Engineer to join its Data & BI team and help i…
providing innovative technology solutions and services to customers. Job Description: Job Title : Forward Deployed Data Engineer (FDE) Job Type : C2C / W2 Experience : 10-15 Years Location : Houston, Texas (Remote) Role…
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…
$87.7k - $139.7k
forward. Position OverviewJLL is seeking an experienced Senior High Voltage Electrical Engineer to lead the design and engineering of critical electrical infrastructure for hyperscale data centers and mission-critical fa…
text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; } Data Engineer Location: Houston, TX | Onsite Interview Process: 2 Virtual Rounds + 1 Onsite Round…
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…
Position Overview We are seeking a Data Engineer with professional retail industry experience to design, build, and maintain scalable data pipelines and data infrastructure supporting data processing, analytics, and repo…
Application Development & Integration, Production Support & QA, and Data Analytics & AI. What You’ll Be Doing: Design and develop... ...solutions. Qualifications: ~2 to 6+ years of data engineering and/or data warehousin…
are committed to developing and sustaining a diverse work force. Job Description The role We are looking for a Data Engineer to build and run the pipelines and data models behind our core data platform — the centralized…
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…
02
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.
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
Ten quiet minutes a day
Applying for data engineer jobs in Houston?
Robbi carries this page into your first day: your role, your city, your shift preference. Then it hands you a few small things each morning and keeps the pipeline honest.
Save what looks right here, then let Robbi hand you a few small things each morning and keep the follow-ups honest.
Start with this search
No email, no resume, no sign-up.
Open your tracker
Everything you saved is already there.