only in your community, but around the world. We believe building engineering is more than systems and structures, it’s about powering... ...where people work, connect, and thrive. From high-performance data centers driv…
Engineering & IT · Seattle, WA
Data Engineer jobs in Seattle, WA
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.
242
Open roles today
$47–$117/hr
Typical pay range
$161k
Median, full-time
12
Fresh in this list
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01
Open data engineer roles
12 shown of 242 · sorted by freshness
$101.3k - $160k
Business Data Technologies (BDT) makes it easier for teams across Amazon to produce, store, catalog, secure, move, and analyze data... ...operating at Amazon scale. This lets BDT customers move beyond the engineering and…
$132.1k - $178.8k
Prime Video's Partner and Content Foundations (PCF) product and data organization obsesses over partners by delivering world-class tools... ...Viewers.Key job responsibilitiesWe are seeking a talented Data Engineer to en…
$114.6k - $234.6k
Service is a new multi-tenant, cloud native service for real-time data integration and replication in heterogeneous IT environments.... ...systems. This cost effective data replication solution is engineered for highest…
provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Position: Data Engineer II Location: Bellevue, WA 98004 Duration: 6 Months Job Type: Temporary Assignment Wo…
$120k - $140k
Section Details Job Title Data Engineer Job Type Full Time Client Location Seattle, WA Work Arrangement Onsite Duration Full Time Pay Rate / Salary $120-$140k/yr....
$89.78k - $112.08k
Company DescriptionRamboll is a global architecture, engineering, and consultancy company. As a foundation-owned people company, founded in... ...play as you support the planning, permitting, and design of data center an…
min, 15-min, hourly, daily), time-zone handling, late-arriving data, and aggregation rules for additive, semi-additive, and ratio-based... ...Analyst and natural-language querying. Work with the data engineering team to…
analytics across the business. It primarily involves partnering with data domain teams to assess and validate table readiness - data... ...well as mentoring team members on semantic modeling and data engineering best pra…
Roles and Responsibilities Design, develop, and configure applications and database solutions using Oracle PL/SQL . Develop, maintain, and optimize complex SQL queries, stored procedures, functions, packages, and databas…
$222.5k - $257.5k
at work, and it’s what we show up for every day.Observability Engineering owns the breadth and depth of observability and telemetry at Smartsheet... .... As a Principal Software Engineer (Observability & Telemetry Data)…
Snowflake Data Engineer Bellevue, WA Responsibilities Design and develop Snowflake Semantic Views for telecom network domains, including logical tables, facts, dimensions, relationships, and metrics. Translate raw networ…
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What data engineers earn in Seattle
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $47–$65 | $98k–$135k |
| Mid level | $65–$90 | $135k–$188k |
| Senior | $87–$117 | $181k–$244k |
Adjusted for the Seattle 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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