Aprio’s Insights & Analytics team is expanding its Microsoft Fabric platform capabilities and is seeking a skilled Power BI & Fabric Semantic Model Architect to lead the design, development, and governance of enterprise-grade semantic models. This role bridges the gap between raw data and business insight—translating complex stakeholder requirements into well-structured, performant data models that power decision-making across the firm.
The ideal candidate is both technically deep and interpersonally strong—someone who can lead and coach a team of report developers, facilitate requirements sessions with business stakeholders, and architect scalable solutions within Microsoft Fabric and Power BI. As Aprio accelerates its AI strategy, this role will play a central part in enabling natural language query (NLQ) capabilities, AI-powered analytics, and Copilot integration across the firm’s reporting ecosystem.
Responsibilities:
- 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
- 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
- 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
- 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
- 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
Semantic Modeling & Architecture
AI, Natural Language Query & Copilot Enablement
Team Coaching & Development
Business & Stakeholder Engagement
Fabric Platform & Governance
Qualifications:
- 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
Preferred Qualifications:
- Microsoft certifications: PL-300 (Power BI Data Analyst), DP-600 (Fabric Analytics Engineer), or DP-100 (Azure Data Scientist)
- Experience with Azure OpenAI Service, Semantic Kernel, or LangChain in analytics or data product contexts
- Exposure to Copilot Studio or Power Automate AI flows for automating insight delivery
- Experience in a professional services or accounting firm environment
- Familiarity with Microsoft Purview for data cataloging, lineage, and AI governance
Core Competencies:
- Data Modeling Proficiency
- Performance Optimization
- AI & NLQ Enablement
- Translating to Tech and Non-Tech
- Analytical Thinking
- Coaching & Mentorship
- Attention to Detail
- Internal/External Team Collaboration
- Strong Communication
- Continuous Learning Mindset
- Business Acumen
- Responsible AI Judgment
Aprio Los Angeles, California, USA Office
21800 Oxnard St., Suite 900, Los Angeles, United States, 94596
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