Business Intelligence Architect
$31,200–$31,200 year
On-siteAtlanta, Georgia, United States
Job Summary
Design and build enterprise semantic models in Microsoft Fabric using Direct Lake mode, Power BI Datasets, and Dataflows Gen2. Author complex DAX measures, calculated columns, and KPI logic following organizational standards while establishing a governed, reusable semantic layer across reporting domains. Lead Aprio's adoption of Power BI Copilot and Microsoft Fabric AI features, including AI-generated report summaries, smart narratives, and anomaly detection. Mentor and coach a team of 4+ report developers, providing technical guidance on best practices, model design, and AI-era BI patterns. 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. Own the semantic model layer within the Aprio Microsoft Fabric Lakehouse architecture, defining and enforcing naming conventions, model governance standards, and AI metadata standards.
Required 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
Desired 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
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