$135k - $150k
Resource Innovations is seeking a Lead Java Software and Data Integration Engineer to join our growing Software as a Service (SaaS) team. As a hands‑on technical lead at Resource Innovations, you will be instrumental in…
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.
361
Open roles today
$38–$96/hr
Typical pay range
$132k
Median, full-time
5
Fresh in this list
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01
Open data engineer roles
12 shown of 361 · sorted by freshness
Job Description Job Description Job Summary: We are seeking an experienced GCP Data Engineer to design, build, and optimize our scalable cloud data platform. In this role, you will architect real-time and batch ELT/ETL d…
$55 - $65 per hour
Title: Data Engineer Location: Tempe, AZ (Onsite) Contract: 12 month Schedule: Monday-Friday | 8:00 AM-5:00 PM Benefits: This position is eligible for medical, dental, vision, and 401(k) . Pay: 55$ - 65$ an hour Position…
Job Description Job Description Your Role • Monitor data center operations and check for emergent alerts through monitoring platforms. • Perform rack and stack installations, ensuring proper power and asset management. •…
COMPANY OVERVIEW: A leading provider of environmental, energy and industrial services POSITION TITLE: Data Center Sales Engineer COMPENSATION: Competitive Salary BENEFITS: Standard package LOCATION: Phoenix, AZ SUMMARY:…
Role Description ~12+ years of experience as a Data Engineer. ~ Design, develop, and maintain scalable, resilient data engineering solutions. ~ Strong expertise in Snowflake, Python, PySpark, DBT, Qlik Replicate, and Air…
Delivery team is a dynamic, cross-functional group of experts in data, technology, GIS, and asset management systems. We deliver... ...This role is intended for an experienced data architecture and engineering profession…
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…
Kforce has a client in Phoenix, AZ who is seeking a Data Engineer to join their team. The Data Engineer is a hands-on technical role focused on designing, developing, and optimizing enterprise data solutions. This indivi…
$50 - $60 per hour
Job Description Job Description Title: Lead Data & AI Engineer Location: Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay: $50-60/hr We’re looking for a Lead Data & AI Engineer to lead the design and delive…
$100k - $115k
Job Description Job Description Job Title: Data Engineer (Mid-Level to Senior) Location: Hybrid / Onsite as needed (project-dependent) Salary: $100,000 - $115,000 We are partnering with an organization seeking a skilled…
more here . Position Summary Virtuous is evolving its data platform into an AI-ready foundation that powers trusted decision... ...across the company. We’re hiring a Lead Data Platform Engineer to design, build, and own…
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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.
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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
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Data Engineer
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Senior Data Engineer
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Staff Data Engineer
05
Data Platform Lead
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