Data Engineer: Build Scalable Pipelines & Lakehouse
Harris ComputerRole Overview
Harris Computer is hiring a mid-level Data Engineer: Build Scalable Pipelines & Lakehouse. This is a full-time role in Wisconsin. Part of Harris Computer's Data Engineering hiring. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job Description
A leading technology provider is seeking a Data Engineer to develop and maintain foundational data infrastructure for their Active Analytics platform. The individual will build data pipelines, ensure data quality, and work closely with analysts to meet data needs. The ideal candidate has 4-6 years of experience with Microsoft Fabric or similar platforms, proficiency in Python or Spark, and a strong understanding of ETL/ELT processes. This role offers competitive benefits and a supportive work environment.
Frequently Asked Questions
How do I apply for the Data Engineer: Build Scalable Pipelines & Lakehouse position at Harris Computer?
Use the Apply button above to submit your application directly to Harris Computer. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Data Engineer: Build Scalable Pipelines & Lakehouse position at Harris Computer located?
This position is based in Wisconsin. Harris Computer has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Data Engineer: Build Scalable Pipelines & Lakehouse at Harris Computer earn?
Harris Computer has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Data Engineer: Build Scalable Pipelines & Lakehouse role at Harris Computer posted?
This role was posted on April 3, 2026 (66 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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