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 · Austin, TX
Data Engineer jobs in Austin, 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.
438
Open roles today
$39–$99/hr
Typical pay range
$135k
Median, full-time
11
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
12 shown of 438 · sorted by freshness
$145k - $165k
consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a... ...tremendous career growth potential. Job Title: Senior Data Engineer - Hadoop Loca…
implementing database schemas, including tables, indexes, views, stored procedures, and triggers to meet business requirements and ensure data integrity.Data Modeling: Creating data models that represent the structure of…
$125k - $191.5k
Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days].The RoleVehicle Data Engineering is looking for a Senior Data Engineer to design, build, and operate dat…
$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…
opportunity to impact your career and provide an adventure where you can push the limits of what's possible.As a Lead Software Engineer - Data and Payments Data Platform at JPMorgan Chase within the Commercial and Invest…
$155k - $175k
consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a... ...tremendous career growth potential. Job Title: Senior Data Engineer Location: 100…
$134k - $180k
Req ID:388878NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be... ...Remote, Texas (US-TX), United States (US).RoleSenior Data Migration Engineer with…
$80.46k - $142.72k
is the world's leading company delivering sustainable design, engineering, and consultancy solutions for natural and built assets.We are... ...you will lead the electrical discipline of multiple concurrent data center pr…
$135k - $160k
consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a... ...career growth potential. Job Title: Real-Time Data Engineer Location: 100% Remote…
Preferred Work Location - Austin, TX / Secondary Work Location - Southlake, TX This role will support analytics, reporting, automation, and data- driven decision support for technology capacity planning working closely w…
Job Description: We are seeking a highly skilled Data Engineer with strong expertise in Snowflake, Python, PySpark, Airflow, and Streamlit to design, build, and support modern cloud-based data platforms. The ideal candid…
02
What data engineers earn in Austin
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $39–$54 | $82k–$113k |
| Mid level | $54–$76 | $113k–$158k |
| Senior | $73–$99 | $152k–$205k |
Adjusted for the Austin 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 Austin?
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.