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Data Engineer jobs in Sacramento, CA
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.
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Open data engineer roles
12 shown of 97 · sorted by freshness
Position titleSenior Data AnalystDescriptionLume Consulting Group is looking for a qualified individual to fill the role of a Data... ...capacity.3.Bachelor's Degree in a Data Analytics, IT-related or Engineering field.*…
DISCRETION OF THE DEPARTMENT AND IS SUBJECT TO CHANGE AS BUSINESS NEEDS ARISE. The Employment Training Panel (ETP) is seeking a Research Data Analyst II (RDA II) in the Planning and Research Unit within the Research and…
detail-oriented technology professional to support California’s emerging Artificial Intelligence (AI) Safety Reporting Program . As a Data Reporting Analyst within the Homeland Security Division’s Policy Branch, you will…
Health (DOSH aka Cal/OSHA), the Analyst II performs complex analytical and technological studies/assignments related to the Cal/OIS data management system. The incumbent works with all programs in DOSH providing guidance…
Job Description and Duties Under general direction of the Research Data Supervisor II (RD Sup II), the Research Data Analyst II (RDA II) is a member of the Research unit responsible for supporting the lead staff over the…
Job Role: Data Engineer with AWS Glue Job Location: Sacramento, CA (Onsite) Job Duration: Long Term Job Summary: We are seeking a highly experienced Senior Snowflake Data Engineer with 10+ years of experience in designin…
the Information Technology Manager II, Chief, Infrastructure Service Branch, the incumbent serves as the Chief of the Storage Engineering & Data Protection Unit. This unit is comprised of Information Technology (IT) prof…
com or call at (***) ***-****. Direct End Client: California Governor's Office of Emergency Services (Cal OES) Job Title: Data Analyst Duration: 36 Months Location: Hybrid / Remote (Candidates must be within 50 miles of…
role, you will have the opportunity to participate in and lead engineering and design of the HVAC and plumbing systems in various types of... ...HVAC and plumbing systems for primarily HyperScale and Colocation Data Cent…
customer service-oriented team environment, surrounded by enthusiastic and self-motivated people, then look no further! Join our BI Data Analytics and Reporting team as an Information Technology Associate and help delive…
international trips to Mexico, Costa Rica, Belize, and the Dominican Republic. Primary Role We are seeking an experienced Senior Data Platform Engineer to architect and scale our data infrastructure. The ideal candidate…
What data engineers earn in Sacramento
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $40–$56 | $84k–$117k |
| Mid level | $56–$78 | $117k–$162k |
| Senior | $75–$101 | $157k–$211k |
Adjusted for the Sacramento market from national ranges.
What employers ask for
The skills these listings keep naming
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.
Resume tips that move the needle
For data engineers specifically — generic advice costs you here
State data scale plainly — rows per day, terabytes managed, pipeline counts — because it is the first thing hiring managers scan for.
Name your orchestration, processing, and warehouse tools per role; the modern stack (Airflow, dbt, Snowflake) is a keyword screen.
Highlight reliability outcomes: pipeline failure rates, data freshness SLAs met, incident reductions.
Show cost work if you have it — warehouse spend is a live concern and optimization stories differentiate.
Mention who consumed your data (analysts, ML teams, executives) to show you build for users, not just movement.
Where this role goes
Typical progression
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