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Roers Companies

Data Engineer

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What they do

A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.

$107,122 / year median in Minnesota

+10% projected growth

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Job Description

Data Engineer Date Posted:
4 September 2026
Closing Date:
October 4, 2026
Recruiter:
Roers Companies Location:
Minneapolis, Minnesota Salary:
USD120,000
to
USD150,000
Job Type & Industry:
Data, Ai & Technology >
Data Engineering Contract Type:
Permanent Job Reference:
2955958570-2 Apply for this job now Job Description Roers Companies is seeking a Data Engineer to design and build scalable data pipelines that power analytics across our real estate portfolio. You will develop and maintain ETL processes, integrate data from property management, finance, and development systems, and optimize our data warehouse in support of business intelligence and reporting. The ideal candidate has strong skills in SQL, Python, and cloud data platforms, and can collaborate with analysts and business teams to model data, ensure data quality, and deliver reliable, well-documented datasets that drive investment and operational decisions. Responsibilities Design, build, and maintain scalable data pipelines and ETL processes Integrate data from property management, finance, and development systems into a centralized warehouse Model and optimize data structures to support analytics and reporting Ensure data quality, reliability, and documentation across all data assets Collaborate with analysts and business stakeholders to understand data needs and deliver solutions Implement and manage cloud-based data infrastructure and tooling Monitor pipeline performance and troubleshoot data issues proactively Support BI dashboards and self-service analytics through curated datasets Required Skills SQLPython ETL development Data warehousing Dimensional data modeling Cloud data platforms (AWS, Azure, or GCP) Data pipeline orchestration (e.g., Airflow or similar) Relational databases Data quality and validation Business intelligence/reporting tools