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
Skills Required
- 5-8 years of experience designing and publishing Power BI semantic models in enterprise environments
- Proficiency in DAX and Power Query (M)
- Hands-on experience with Microsoft Fabric (OneLake, Lakehouses, Dataflows Gen2, Direct Lake mode)
- 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
- Experience coaching or mentoring junior analysts or developers
- Ability to gather, document, and translate business requirements into data models and AI-readiness roadmaps
- Familiarity with data governance, row-level security (RLS), dataset certification, and Power BI deployment pipelines
- Strong communication skills and ability to explain technical concepts to non-technical audiences
- Understanding of responsible AI principles, data privacy, and AI output auditability
- Microsoft certifications: PL-300, DP-600, or DP-100
- Experience with Azure OpenAI Service, Semantic Kernel, or LangChain
- Exposure to Copilot Studio or Power Automate AI flows
- Experience in a professional services or accounting firm environment
- Familiarity with Microsoft Purview for cataloging, lineage, and AI governance
Aprio Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Aprio and has not been reviewed or approved by Aprio.
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Fair & Transparent Compensation — Pay is generally positioned as competitive and fairly paid across many roles, with clearer benchmarking helped by public job-posted ranges and compensation aggregators.
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Healthcare Strength — Health, dental, and vision coverage is positioned as comprehensive and available from day one for full-time hires, which is stronger than the more typical waiting-period approach.
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Retirement Support — Retirement offerings include a 401(k) with profit sharing and access to FSA/Dependent Care accounts, which can improve total rewards when firm performance supports contributions.
Aprio Insights
What We Do
Aprio is a premier CPA and business advisory firm that advises clients and associates on how to achieve what’s next. Aprio’s associates work as integrated teams across advisory, assurance, tax, outsourcing, staffing and private client services, bringing the best thinking and personal commitment to each client. Across practices, Aprio brings together proven expertise, deep understanding and strategic foresight for industries including Manufacturing and Distribution; Non-Profit and Education; Professional Services; Real Estate and Construction; Retail, Franchise and Hospitality; and Technology and Blockchain. Headquartered in Atlanta, Georgia, Aprio has grown to over 1,000+ team members. To serve clients wherever life or business may take them, Aprio’s teams speak more than 30 languages and work with clients in over 50 countries.









