Data Engineer

Do you love working with talented people? So do we!

Our team is growing and we’re looking for best-in‑class talent. We value experienced, career‑minded employees who focus on teamwork, professionalism and an unparalleled commitment to customer service. We offer full‑time employees a competitive benefits package that includes health, dental and vision insurance, along with life and AD&D insurance, 401k plans, vacation time and more.

Browse positions available at mSupply and throughout our HVAC, plumbing and appliance parts business units nationwide. Use the filters to narrow by department, business unit or location.

Location: REMOTE

Job
-mSupply

# of Openings: 1

mSupply is North America’s leading distributor of OEM repair parts and equipment, serving professionals in the appliance, HVAC, plumbing, commercial kitchen, and pool/spa industries. Headquartered in St. Louis, MO, mSupply is a multi‑billion‑dollar enterprise offering an extensive product range, industry expertise, and seamless service. With more than 2,000 associates across the U.S. and Canada, mSupply’s family of brands delivers with speed, reliability, and precision through its branches, distribution centers, and extensive fleet of delivery vehicles.

Shipped orders reach 93% of U.S. customers via next‑day ground delivery and 100% within two days. For more information, visit

The Data Engineer supports the build‑out and day‑to‑day operations of mSupply’s enterprise data platform on Microsoft Fabric. Working under the guidance of the Senior Data Engineer and Senior Manager of Data Platform, this role contributes to pipeline development, data quality monitoring, and platform maintenance across the medallion architecture (Bronze, Silver, Gold).

• Build and maintain ELT/ETL pipelines that ingest data from source systems into Microsoft Fabric, following established patterns and standards.
• Develop, test, and document dbt models across the Bronze, Silver, and Gold layers, ensuring data quality and transformation accuracy.
• Monitor pipeline runs and data freshness dashboards, triaging failures, investigating root causes, and escalating as needed.
• Write and optimize SQL queries and Python scripts for data transformation, validation, and ad hoc analysis.
• Assist with onboarding new data sources, including mapping source schemas, building ingestion pipelines, and validating initial data loads.
• Support Fabric Pipelines, Notebooks, and Dataflows for orchestration, scheduling, and error handling.
• Contribute to data quality by writing and maintaining dbt tests and working with upstream system owners to resolve data issues.
• Help maintain CI/CD pipelines for dbt and Fabric workloads, including pull request reviews and automated test execution.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related field, or equivalent practical experience.
• 1‑3 years of experience in data engineering, analytics engineering, software development, or a related technical role (internship experience counts).
• Proficiency in SQL for querying, transforming, and analyzing structured datasets.
• Working knowledge of Python for scripting, data manipulation, or pipeline development.
• Foundational understanding of data modeling concepts and relational database design.
• Familiarity with version control systems (Git) and collaborative development workflows.

• Exposure to cloud‑based data platforms such as Microsoft Fabric, Azure Synapse Analytics, or Azure Data Factory.
• Familiarity with dbt or similar data transformation frameworks.
• Experience working with ELT/ETL pipelines or data orchestration tools.
• Understanding of medallion or multi‑layer data architectures (Bronze, Silver, Gold).
• Background in wholesale distribution, supply chain, or related B2B industries.
• Experience or demonstrated ability using AI‑powered tools (e.g., code assistants, LLMs, AI‑augmented workflows) to accelerate work and improve outcomes.

This is a full‑time position. Duties are primarily performed in an office or remote work environment.

• Primarily sedentary work with…