ETL Data Engineer Austin, TX Onsite Only Locals One year contract We are seeking candidates who do not require visa sponsorship, are eligible to work on a W2 Position is ONSITE at the location listed above (NO REMOTE WOR…
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.
502
Open roles today
$39–$99/hr
Typical pay range
$135k
Median, full-time
4
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Open data engineer roles
12 shown of 502 · sorted by freshness
Skills: Snowflake and Data pipelines Python AI/ML and Advanced Analytics Building and deployment AI agents... ...with the Operations team, as well as data scientists and software engineers, on Python-based applications,…
Hi , Data Engineer Location Austin, TX Skills: Proven hands-on experience in Snowflake database . Must have - Proven hands-on experience in working on solutions using Apache Doris. Proficient in data modeling and writing…
Overhaul is a supply chain integrity solutions company that allows shippers to connect disparate sources of data into the first fully transparent situational analysis engine designed for the logistics industry. Data that…
$37 per hour
Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system. In this role, as an AI Pilot – that’s ho…
Senior Databricks Data Engineer (Azure Databricks | Lakehouse | ETL/ELT) Austin, Texas (Hybrid – 3 Days Remote | Onsite Every Monday & Thursday) Experience: Minimum 12+ Years Mandatory Requirements ✔ Databricks Certified…
We are currently looking for a Data Engineer for a 100% remote position on a large federal government project. This role focuses on designing, developing, and maintaining scalable data solutions that support healthcare o…
culture that supports personal and career development in a fun, casual, and collaborative environment. Who We Want As a Senior Data Engineer at Arrive Logistics, you will build and own the data ecosystem that powers our…
Description: ABOUT TRUDATARX TruDataRx, Inc. uses objective clinical data to help clients improve the clinical efficacy and reduce the... ...POSITION SUMMARY: We are seeking an experienced Data Engineer to architect, bui…
Job Description Job Description As an early hire to our engineering team, you will be responsible for managing Loxo’s data integration function. You will be primarily responsible for migrating new clients’ legacy data fr…
$65 - $69.72 per hour
Job Description Job Description Data Science Engineer Job Details Data Science Engineer (Contract) Location: Austin TX, 78758 (Hybrid) Duration: 11/17/2025 to 11/13/2026 Team: Fraud ADUS Key Responsibilities: Develop and…
with unmatched rewards as we transform the hospitality and experiences industry globally. We are seeking an experienced Senior Data Engineer to establish and lead our data infrastructure as an early member of our data te…
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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.
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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
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Data Engineer
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Senior Data Engineer
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Staff Data Engineer
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Data Platform Lead
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