Data Engineer

City Wide Facility Solutions•Lenexa, KS

11h

About The Position

City Wide Facility Solutions is seeking a Data Engineer to join our growing IT team! In this role, you’ll play a key part in designing, building, and maintaining our enterprise data environment—ensuring data flows seamlessly from our MS Dynamics applications to the Fabric Lakehouse. You’ll use your technical expertise and curiosity to transform complex data into meaningful insights that drive better business decisions.

Requirements

Bachelor’s degree in Computer Science, Data Science/Analytics, Economics, or a related field.
5+ years of experience in data analytics, engineering, or warehouse management.
Strong experience with Fabric Lakehouse, SQL Server Management Studio, Azure SQL, SSIS (or similar ETL tools), and Windows environments.
Solid understanding of ELT/ETL development and data modeling best practices.
Proven ability to analyze large datasets and translate findings into actionable insights.
Excellent communication and teamwork skills, with a proactive approach to problem-solving.
Candidate must be located in the Kansas City Metropolitan area, and no relocation offered at this time.

Responsibilities

Design, develop, and maintain scalable data environments to support reporting, analytics, and AI/ML initiatives.
Build optimized data schemas that power intuitive reporting in Power BI and similar tools.
Create and maintain ETL/ELT pipelines and notebooks to ingest, transform, and model data from multiple sources into our Fabric data platform.
Monitor and improve data quality, performance, and reliability across systems.
Collaborate with cross-functional teams to ensure data structures align with business goals and analytical needs.
Apply AI/ML techniques to enhance data accuracy and produce predictive insights.
Support analysts and leadership by developing dashboards, visualizations, and ad hoc reports.
Document data sources, transformations, and flows to ensure transparency and consistency.
Research and recommend emerging tools and technology to improve data processes.