Microsoft Fabric Data Analyst

* Description
* Our client is looking to hire a direct placement or contract to hire Microsoft Fabric Data Analyst to their team. Our client is continuing its data transformation journey and is looking to hire a full-time Microsoft Fabric Data Analyst to help drive their enterprise data strategy forward. They are open to remote candidates, but they will need to travel to Appleton, WI once a quarter.

If they are local to the area, that would be preferred. The Analyst will work closely with the product owner, who currently wears multiple hats and is the only in-house member of the data warehouse team. We placed someone in this same role in November of 2025. The ideal candidate will be assigned to one or more business units, such as HR or Finance, and will be responsible for gathering requirements, digging into data sources, and building out data models in Microsoft Fabric.
This person must bring hands-on experience with Fabric-not just familiarity with similar platforms-and be ready to take ownership of the existing solution and expand it. Strong Power BI skills are essential for creating visualizations that support enterprise reporting. The role also requires a collaborative mindset, a willingness to jump in and support service tickets, and the ability to guide stakeholders while keeping the vision on track amidst competing voices.

Our client is consolidating data across its organization and newly acquired company, KASE, and is committed to building a best-in-class data environment. Data governance is on the roadmap, and this analyst will play a foundational role in shaping that future. Above all, our client values humility, leadership, and a proactive approach-so candidates should be ready to "check their ego at the door" and help build something great.

Job Description:

We is accelerating a modern, AI-centered data platform on Microsoft Fabric. We're hiring a Data Analyst who can translate business questions into reliable, decision-ready insights-fast. You'll partner daily with Finance, Operations, Customer Service, and HR, shaping requirements, validating data, and delivering clear, print-friendly Power BI reports and self-service datasets. You'll work side-by-side with Data Engineers to convert curated warehouse tables into trusted metrics, dashboards, and narratives that drive action across business units (Fulfillment, Traditional, Chemical, Transportation).
Must-haves:

* SQL (strong): confidently join across multiple sources and very large tables (many columns, million + rows); write efficient queries (filters before joins, window functions, CTEs where appropriate), and interpret query plans to tune performance.

* Data sourcing & mapping: define and maintain source-to-target mappings, conformed dimensions/keys, lineage, and KPI definitions; reconcile semantics across systems to ensure one version of the truth.

* Cross-source storytelling: pull data from multiple systems to deliver a single, coherent narrative and self-service dataset; shape a consistent, print-friendly user experience end-to-end.

* Power BI: semantic modeling, DAX, RLS, usability, and visualization best practices.

* Business partnership: engage Finance, Operations, Customer Service, and HR to clarify definitions, prioritize needs, and iterate quickly.

* AI in the loop: use Copilot for Power BI/Fabric and other AI tools to speed analysis, documentation, and the end-user experience.
What You'll Do

* Partner with the business:
Run structured discovery with Finance, Operations, Customer Service, and HR; translate goals into well-defined KPIs, dimensional definitions, and acceptance criteria.

* Model for analysis:
Shape semantic models and Power BI datasets (relationships, DAX measures, hierarchies, RLS) that align to curated warehouse/lakehouse tables delivered by Engineering.

* Build decision-ready visuals:
Create readable, print-friendly reports and dashboards (executive summaries, drill-downs, paginated layouts when needed) that answer the "so what?"

* SQL-driven analysis:
Profile data quality, reconcile totals, trace lineage, and author performant queries to validate numbers and accelerate insight generation.

* UAT & data quality:
Define test cases, execute user acceptance testing, reconcile to source systems (WMS/OMS/ERP/HRIS), and document known caveats and SLAs.

* AI-assisted workflows:
Use Copilot/NLQ to draft measures, generate narrative summaries, create how-to guides, and surface "explain this insight" experiences.

* Documentation & enablement:
Maintain data dictionaries, KPI definition sheets, and short "how to use this report" guides; run training for power users and frontline managers.

* Adoption & support:
Monitor usage, gather feedback, prioritize enhancements, and partner with Data Engineers to address data gaps or performance issues.

* Governance & security:
Apply RLS/OLS, certify datasets, tag sensitivity, and contribute to catalog/lineage so users can trust what they're using.

Required Qualifications

* 3+ years in analytics, BI, or…