Data & Analytics Engineer

Are you looking for a full-time position that offers a great work-life balance, competitive salary, and company culture?

Do you favor a relaxed, collaborative office environment over corporate stuffiness?

At JMP, you’re more than an employee—you are an owner! By taking part in our employee-owned stock option plan (ESOP) and 401k you’ll be on the road to financial security and well-planned retirement.

JMP is one of the largest commercial HVAC sales reps in the Southeast, representing over 30 top brands of equipment, including Xylem, Lochinvar, Baltimore Aircoil Company, and Climate Master. We have an unprecedented 65-year reputation for engineered equipment sales & support and unparalleled client education programs.

We believe in doing right by our clients and our co-workers by being helpful, courteous, and honorable.

The Data & Analytics Engineer designs, builds, and supports data and reporting solutions that help drive business decisions across the organization. This role will be working with Microsoft Fabric, Power BI, SQL, and data pipelines to deliver trusted analytics, reliable data models, and actionable insights.

• Strong SQL/T-SQL skills, including joins, common table expressions, aggregations, window functions, data validation, and query troubleshooting.
• Python or PySpark for data preparation, validation, notebooks, or automation.
• Hands‑on Power BI development experience, including Power Query, semantic models, interactive report design, publishing, and refresh support.
• Understanding of dimensional modeling, including fact tables, dimension tables, star schemas, grain, keys, and slowly changing dimensions.
• Understanding of ETL and ELT concepts, data ingestion, transformation, orchestration, dependencies, and error handling.
• Ability to reconcile data from source systems through transformation layers to published reports.
• Experience creating clear technical documentation and translating business definitions into governed analytical logic.
• Working knowledge of security concepts that affect analytics, including access management and row‑level security.
• Basic Git or Azure Dev Ops source‑control practices.
• Strong communication with technical and non‑technical audiences.

• Fabric work spaces, capacities, items, and deployment concepts.
• Lakehouse and Warehouse design and support.
• Data Factory pipelines and Dataflows Gen
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• Fabric notebooks and Spark or Python for data engineering tasks.
• One Lake concepts, shortcuts, and medallion‑style data organization.
• Direct Lake and Import semantic‑model considerations.
• Monitoring Hub, refresh troubleshooting, lineage, and operational support.
• Deployment pipelines, source control, or structured development and release practices.
• Advanced calculation patterns.
• Power Query and reusable transformation logic.
• Semantic‑model performance optimization and model simplification.
• Row‑level security and testing across business entities or user groups.
• Workspace organization, Power BI apps, deployment, and access management.
• Report usability, accessibility, visual consistency, and performance optimization.
• Shared semantic models and thin‑report development patterns.
• Power Shell for administration or repeatable support tasks.
• Ability to work with REST APIs, JSON, authentication concepts, and configuration values.
• Ability to read, troubleshoot, and adapt existing code without needing to be a full‑stack developer.

Requires periodic travel to the home office, located in Greensboro, NC.