$75k - $85k
algorithm development. We need strong practical skills in analyzing data, especially battery testing datasets. We require proficiency... ...is an advantage. A degree in Data Science, Electrical Engineering, Computer Scie…
Engineering & IT · San Jose, CA
Data Engineer jobs in San Jose, 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.
428
Open roles today
$52–$129/hr
Typical pay range
$178k
Median, full-time
11
Fresh in this list
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01
Open data engineer roles
12 shown of 428 · sorted by freshness
$176.1k - $308.2k
enterprises face: who can and should take what action on what data. Veza's Access Graph platform maps an organization's entire identity... ...applications, data, cloud environments, and AI agents. For engineers joining V…
Job-ID27801708Reference26-07957Remote100% Remote Job Title: Contract Data Engineer (API & Database Focus) Role Summary: We are seeking an experienced and highly skilled Contract Data Engineer. This role is focused on bui…
$245k - $331.5k
opportunity to prosper. We never stop working to find new, innovative ways to make that possible.Job OverviewThe Fintech Principal Data Engineer bridges data needs between data producers (Fintech product teams) and data…
We are seeking an experienced Kinaxis Data Migration Engineer with 8–10 years of experience in data migration, supply chain systems, data analysis, and enterprise data integration. The ideal candidate will have strong kn…
$159.2k - $301.6k
About the roleAdobe’s Security Data Platform team builds and operates a petabyte-scale security data lakehouse that turns enterprise... ...investigations, compliance, and security analytics.As a Staff Security Data Engin…
$51 - $61 per hour
DescriptionA client with Kforce is seeking a Data Engineer II to join their team in Mountain View, CA.Summary:We are looking for creative problem solvers with a passion for tackling tough customer problems involving data…
$144.4k - $234k
PermanentCompany: WalmartBusiness Segment: Home OfficePosition: Senior Data EngineerJob Location: 1375 Crossman Avenue, Sunnyvale, CA 94089... ...and actionable insights. Owns end-to-end delivery of data engineering task…
chance to be part of something exceptional.Job title: (Senior) Data Scientist / ConsultantLocation: Remote (USA)About the RoleAt Centric... ...: you are the go-to contact for data science and data engineering topics.Keep…
Position: Data Engineer Location: SAN JOSE, CA***Onsite*** Duration: 1 Years Job Title: Machine Learning Engineer (Generative AI & Cloud) The Opportunity We are seeking a talented and experienced Machine Learning Enginee…
Hiring Alert | Kinaxis Data Migration Engineer Location: Remote (USA) Employment Type: Full-Time Experience Required: 8 10 Years Must-Have Skills: Data migration analysis and execution for Kinaxis environments Source sys…
Job Title : Kinaxis Data Migration Engineer Location: Remote Position Type: Fulltime Experience Required:8+ Job Description Analyze source systems and identify data required for migration into Kinaxis. Understand supply…
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What data engineers earn in San Jose
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $52–$72 | $108k–$149k |
| Mid level | $72–$100 | $149k–$207k |
| Senior | $96–$129 | $200k–$269k |
Adjusted for the San Jose 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.
04
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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