Power BI Architect

Responsibilities:

• Lead the design, review, and refinement of Power BI semantic models that provide a reliable foundation for enterprise reporting and analytics.

• Examine semantic models produced by external development teams and confirm they meet architectural standards, data quality expectations, and business objectives.

• Assess AI-generated modeling outputs to determine whether they deliver meaningful and accurate business results, not just technically valid structures.

• Advise stakeholders and technical teams on data modeling best practices, governance considerations, and effective architectural options for Power BI environments.

• Serve as a strategic resource for leadership by validating recommendations, challenging assumptions, and offering informed guidance on semantic modeling decisions.

• Identify opportunities to improve large-scale semantic models that support reporting needs across multiple business regions and functions.

• Collaborate with teams involved in the transition from Tableau to Power BI to help align semantic model design with future reporting needs.

• Evaluate how platforms such as Microsoft Fabric or OneLake may support performance, scalability, and integration between Snowflake and Power BI.

• Work within a data ecosystem that consolidates information from multiple enterprise platforms, including Dynamics and internally developed systems, into Snowflake.

Requirements

• Strong experience architecting and optimizing semantic layers and data models within Microsoft Power BI environments.
• Proven ability to evaluate complex enterprise reporting models for accuracy, scalability, and alignment with business requirements.
• Hands-on knowledge of Snowflake as a core analytics data platform.
• Familiarity with Tableau and experience supporting or advising on Power BI migration initiatives.
• Understanding of Microsoft Fabric and its potential role in modern analytics architecture.
• Ability to assess technical recommendations critically and communicate clear guidance to leadership and delivery teams.
• Experience working across complex data landscapes that integrate multiple source systems into a unified reporting environment.