refusing to choose between performance and sustainability, design and engineering, ambition and integrity. In Lucid Air and Lucid Gravity, we... ...and shape the future of mobility.About the Team The ADAS Data Infrastruc…
Engineering & IT · Detroit, MI
Data Engineer jobs in Detroit, MI
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.
173
Open roles today
$35–$87/hr
Typical pay range
$120k
Median, full-time
3
Fresh in this list
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01
Open data engineer roles
12 shown of 173 · sorted by freshness
transportation on a global scale.. The Role Our Product Safety Data Analytics team is seeking an experienced AI/ML Data Scientist... ...Qualifications) Bachelor's degree in Computer Science, Engineering, Mathematics, or…
transportation on a global scale. The Role The Resource Demand team is building trusted data pipelines, analytical datasets, and reporting applications that improve engineering planning decisions across General Motors. T…
The Role General Motors is seeking a Data Analyst to support the GPSC Logistics & Packaging organization. This role sits in the business... ...Partner cross-functionally with Purchasing, PFEP, packaging engineers, contai…
Job Description Job Description Job Title: Data & Reporting Analyst Location : Southfield, MI (Fully in-person) Job type : Full Time Role Summary The Data & Reporting Analyst is responsible for transforming complex opera…
portfolio analytics experience - A minimum of three (3), and preferably four to seven (4-7) years, of professional experience in data engineering, business intelligence, data analytics, or a related information technolog…
$150.5k - $245.5k
on more meaningful work. We focus on developing and improving data pipelines, infrastructure, architecture, and analytic tools to... ...allow resources to fuel our transformation. Working with a team of engineers, analys…
Band: Professional Job Summary The EGTM Analyst owns the measurement and monitoring of the GTM Blueprint, turning performance data into clear insights, action plans, and enterprise visibility. This role compiles and publ…
position will be posted until filled About the role The Data Analyst II is responsible for collecting, analyzing, and interpreting... ...Partner effectively with business stakeholders, IT teams, data engineers, and other…
a technical expert and project leader for the most challenging data science projects. Provides highly technical and analytical assessments... ...of a quantitative nature (e.g., Statistics, Computer Science, Engineering,…
Technology Management, we're transforming how businesses harness data to drive innovation and informed decision-making. As leaders in... .... We're seeking a Senior Full-Stack BI Architect / Fabric Data Engineer to desig…
$140k - $200k
– Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and... ...them within 1 week. Overview We're looking to hire for our Data side of our AI…
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What data engineers earn in Detroit
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $35–$48 | $73k–$100k |
| Mid level | $48–$67 | $100k–$140k |
| Senior | $65–$87 | $135k–$181k |
Adjusted for the Detroit 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
01
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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