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Semantic Modeling & Architecture 

• Design and build enterprise semantic models in Microsoft Fabric using Direct Lake mode, Power BI Datasets, and Dataflows Gen2 
• Develop well-structured star and snowflake schemas optimized for Power BI performance, NLQ discoverability, and Copilot compatibility 
• Author complex DAX measures, calculated columns, and KPI logic following organizational standards; ensure measure naming and descriptions support AI-assisted querying 
• Establish and maintain a governed, reusable semantic layer across reporting domains (finance, operations, marketing, HR, growth) 
• Evaluate and implement incremental refresh, aggregations, and query reduction strategies 
• Architect semantic models to support natural language query (Q&A, Power BI Copilot, Azure OpenAI integration) by enforcing descriptive field names, synonyms, and measure annotations 
• Define and maintain Q&A synonyms, linguistic schemas, and field-level descriptions that enable accurate AI-driven query interpretation 

AI, Natural Language Query & Copilot Enablement 

• Lead Aprio's adoption of Power BI Copilot and Microsoft Fabric AI features, including AI-generated report summaries, smart narratives, and anomaly detection 
• Design semantic models and data products with AI-readiness in mind-ensuring metadata quality, field descriptions, and schema consistency support large language model (LLM) integrations 
• Collaborate with IT and data engineering to evaluate and implement natural language query interfaces, including Power BI Q&A, Copilot for Microsoft 365, and Azure OpenAI Service connections to Fabric data 
• Develop prompting strategies and governance guardrails for AI-generated insights to ensure accuracy, auditability, and alignment with firm standards 
• Evaluate emerging Microsoft AI capabilities (Fabric Workload Hub, Copilot Studio, OneLake AI catalog) and provide architectural recommendations for phased adoption 
• Partner with business stakeholders to identify high-value use cases for AI-assisted analytics, self-service insights, and conversational BI 
• Educate and upskill team members and business users on responsible use of AI tools within the BI ecosystem 

Team Coaching & Development 

• Mentor and coach a team of 4+ report developers, providing technical guidance on best practices, model design, DAX, and AI-era BI patterns 
• Conduct code and model reviews, establishing a culture of quality and continuous improvement 
• Create internal documentation, standards guides, and reusable component libraries for the team 
• Support onboarding of new team members and facilitate skill development in Power BI, Fabric, and emerging AI analytics tools 

Business & Stakeholder Engagement 

• Lead requirements-gathering sessions with business stakeholders, translating needs into data model specifications and AI-assisted analytics roadmaps 
• Serve as a trusted advisor, clearly communicating model design decisions, tradeoffs, and AI capability opportunities to executive and non-technical audiences 
• Collaborate with data engineers, DevOps, and business analysts to ensure analytical models support downstream use cases including Copilot and self-service BI 
• Champion data literacy and responsible AI use across the organization in collaboration with the data governance manager and data governance committee 

Fabric Platform & Governance 

• Own the semantic model layer within the Aprio Microsoft Fabric Lakehouse architecture (OneLake, Lakehouse, Notebooks) 
• Define and enforce naming conventions, model governance standards, certification processes, and AI metadata standards for published datasets 
• Coordinate with the data engineering team to ensure clean, well-documented source data is available for modeling and AI consumption 
• Monitor model health, performance, and usage via Power BI Admin portal and Fabric Monitoring Hub 
• Ensure compliance with data security, row-level security (RLS), and data privacy requirements across all published models and AI-accessible data products 
• Establish AI governance practices including prompt auditability, output validation standards, and acceptable use policies for AI-generated content within BI workflows 

• 5-8 years of experience designing and publishing Power BI semantic models in enterprise environments 
• Proficiency in DAX, Power Query (M), and data modeling concepts (star schema, relationships, cardinality) 
• Hands-on experience with Microsoft Fabric (OneLake, Lakehouses, Dataflows Gen2, Direct Lake mode) 
• Demonstrated experience with Power BI Q&A, linguistic schema authoring, and synonym configuration for natural language query 
• Familiarity with Power BI Copilot, Microsoft 365 Copilot, or Azure OpenAI Service integrations with Fabric data sources 
• Demonstrated ability to gather, document, and translate business requirements into data models and AI-readiness roadmaps 
• Experience coaching or mentoring junior analysts or developers 
• Strong communication skills with the ability to explain technical concepts-including AI capabilities and limitations-to non-technical audiences 
• Familiarity with data governance, RLS, dataset certification, and Power BI deployment pipelines 
• Understanding of responsible AI principles, data privacy considerations, and AI output auditability in enterprise analytics contexts