$149k - $189k
,000 per year Requirements: We require an MS in Mechanical Engineering or a related thermal sciences discipline; a PhD is preferred.... ...of relevant experience in thermal systems, HVAC/R, hydronics, data center cooling…
Engineering & IT · Milwaukee, WI
Data Engineer jobs in Milwaukee, WI
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.
68
Open roles today
$36–$89/hr
Typical pay range
$123k
Median, full-time
9
Fresh in this list
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01
Open data engineer roles
12 shown of 68 · sorted by freshness
$100k - $140k
Salary: $100,000 - 140,000 per year Requirements: We require six or more years of professional experience in data engineering, data operations, data platform operations, or a related discipline. We prefer a bachelors deg…
secrets to our success -- so we give you unlimited access to everything you need to create innovative new solutions on our engineering team. As a Sr. Data Engineer, you will design, build, and support scalable data solut…
We are looking for a Data Engineer to help shape and expand a cloud-focused data environment that supports analytics, operational reporting, automation, and emerging AI use cases. Based in Brookfield, Wisconsin, this pos…
Senior Snowflake Data Engineer / Architect with Cortex AI Job Summary We are seeking a Senior Snowflake Data Architect with strong hands-on experience in Snowflake, data architecture, dimensional modeling, SQL, and enter…
resources of the fastest-growing brand in the construction industry to make it happen.Your Role on Our Team:The Senior Manager of Data Engineering leads teams that design, build, operate, and continuously improve enterpr…
$132.26k - $155.6k
all from Day One.Job DescriptionJob Duties -Responsible for big data/ analytics projects that gather and integrate large volumes of... ...in a quantitative field such as statistics, computer science, engineering or appli…
We are seeking a highly experienced Senior Snowflake Data Architect with strong expertise in enterprise data architecture, analytics... .... The architect will work closely with technical leaders and engineering teams to…
processes that run it. That work changes the operating model an engineering organization runs on, the ways of working underneath it, and... ...We combine our strength in technology and leadership in cloud, data and AI wi…
Establishes and implements appropriate standards and criteria for data security requirements * Design, develop, deploy and manage... ...Qualifications * Bachelor’s degree in computer science, computer engineering, softwa…
Data Security Engineer About the Opportunity AEBS is seeking a talented cybersecurity professional to help protect sensitive data across enterprise systems and platforms. The Data Security Engineer role offers the opport…
$131.6k - $249.78k
relevant experience in the design, development, and evaluation of Data Platform solutions such as Data Warehouses, Data Lakes, and... ...requirements Contribute to the vision and strategy for data engineering, ensuring a…
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What data engineers earn in Milwaukee
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $36–$50 | $74k–$103k |
| Mid level | $50–$68 | $103k–$142k |
| Senior | $66–$89 | $138k–$185k |
Adjusted for the Milwaukee 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
02
Data Engineer
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Senior Data Engineer
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Staff Data Engineer
05
Data Platform Lead
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