Data Engineer Location: Orlando, FL or Los Angeles, CA Must be willing to relocate/work onsite (2 weeks' notice from time of offer accept) Zero exceptions will be made, as this is corporate policy - no delayed remote sta…
Engineering & IT · Los Angeles, CA
Data Engineer jobs in Los Angeles, 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.
540
Open roles today
$46–$114/hr
Typical pay range
$157k
Median, full-time
5
Fresh in this list
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01
Open data engineer roles
11 shown of 540 · sorted by freshness
$150k - $230k
you’re exactly who we’re looking for. The Role Hadrian's Data Analytics team builds and owns the semantic layer that every... ...act on. You'll build it in close partnership with Data Platform Engineering, Data Analysts,…
Senior Data Engineer Core Data Platform Location: Burbank, California-Onsite Job Type: Full-Time, Permanent About the Opportunity Our client is seeking an experienced Senior Data Engineer to join a high-performing engine…
$130k - $170k
manufacturers. Our success rate is unmatched by any other Firm. Strategic Legal Practices is seeking a self-starting Senior Data Engineer to help shape how a high- impact litigation firm leverages data. In this role, you…
$89k - $119.3k
past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and adva…
Job Description Job title: Senior Data Engineer Experience: 8-15 Years Location: Glendale, USA Job Type: Full-time Must Haves ~5+ years of Strong experience with Core Data Platform/Data Engineering. ~ Data Modeling (Dime…
Job Description Job Description We're working with a growing home furnishings retailer that's modernizing its data infrastructure - think legacy SQL Server systems evolving into cloud-native pipelines feeding BI and emer…
$105k - $200k
Job Description Job Description Description We are currently seeking highly motivated Data Engineers at various levels. This role will report to the Director - Data Engineering and work closely with data analysts, data e…
$110.4k - $165.6k
that matter – both for our audiences and our employees – and aim to leave a positive mark on culture. Overview As a Senior Data Engineer, you will play a pivotal role in driving our data strategy and standard methodologi…
$130k - $150k
Apply now: Lead Data Engineer / Delivery Lead, location is in LA. The start date is ASAP for this contract position. Job Title: Lead Data Engineer / Delivery Lead Location-Type: LA Start Date Is: ASAP Duration: Contract…
$170k - $240k
easy for anyone to create original music. Built by musicians and engineers, Suno empowers users to turn ideas into fully produced tracks... ...and uniquely yours. About the Role We’re seeking talented data engineers to j…
02
What data engineers earn in Los Angeles
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $46–$63 | $95k–$132k |
| Mid level | $63–$88 | $132k–$183k |
| Senior | $85–$114 | $177k–$238k |
Adjusted for the Los Angeles market from national ranges.
03
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.
05
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.
03
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.
05
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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