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Engineering & IT · Phoenix, AZ
Data Engineer jobs in Phoenix, AZ
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.
141
Open roles today
$38–$96/hr
Typical pay range
$132k
Median, full-time
7
Fresh in this list
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01
Open data engineer roles
12 shown of 141 · sorted by freshness
Role – GCP Data Engineer Location – Phoenix, AZ Duration: 12+ Months Skills: Years of experience : 5-7 years GCP Cloud : GCS, DataProc, BigQuery, Composer/Airflow Big Data: PySpark Spark, Python, GCP is must have Strong…
Solution IT Inc. is looking for GCP Data Engineer for one of its clients in Phoenix, AZ / Charlotte, NC / Salt Lake City, UT Job Title: GCP Data Engineer Required skills: Hands-on experience with GCP - Big query, DAG, Pu…
Complex Systems: Connect with internal backend services, third-party APIs, and data sources across a distributed architectureCollaborate Cross-Functionally: Work closely with mobile engineers, product managers, designers…
$103.75k - $174.75k
the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success... ...through building and leveraging innovative technology and data insights.…
$144.25k - $256.25k
annually + bonus + equity (if applicable) + benefitsJob Function: Engineering & ArchitectureSchedule: Full timeShift: DayWorkplace:... ...productionStrong engineering fundamentals across backend systems, APIs, data pipel…
$123k - $215.25k
StatesSalary: $123000 - $215250 annually + bonus + benefitsJob Function: Engineering & ArchitectureSchedule: Full timeShift: DayCareer Area:... ...-grade agentic systems that operate on real financial data, serve real cu…
$40 per hour
job summary: We are seeking an experienced Databricks Data Engineer to join our high-performing Data & AI practice in Phoenix, AZ. In this role, you will be responsible for designing and deploying enterprise-grade Lakeho…
$86.72k - $119.24k
Summary Corning is developing the future of solar module manufacturing in Tolleson, AZ, and we're looking for a Manufacturing Data Engineer to build the data, reporting, and analytics foundation from the ground up. This…
Data Engineer All IT Solutions United States · Phoenix, Arizona Workplace Type — Remote Employment Type — Contract We are currently seeking a qualified Data Engineer to support this engagement. Please review the complete…
We are seeking a Senior OCI Engineer to design, build, and govern enterprise Oracle Cloud environments. The role will lead OCI Landing Zone implementation, cloud governance, security architecture, automation, and technic…
We are seeking an experienced Cloud Data Security Assessment Consultant with strong expertise in Google Cloud Platform (GCP) security, data protection, application security, and security architecture assessments. The rol…
02
What data engineers earn in Phoenix
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $38–$53 | $80k–$110k |
| Mid level | $53–$74 | $110k–$153k |
| Senior | $71–$96 | $148k–$199k |
Adjusted for the Phoenix 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
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.
02
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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