Data architecture · Semantic intelligence · AI analytics
Data & AI Analytics Architect with 12+ years across enterprise data platforms, Microsoft Fabric, semantic layers and models, business ontologies, executive analytics, and AI-powered decision systems.
Featured build
I designed and built an AI-powered analytics application on top of Microsoft Fabric that combines governed semantic-model access with business knowledge and ontology, then returns branded analytical answers rather than generic chat responses.
The application gives AI controlled access to trusted enterprise metrics and business context, allowing it to retrieve data, derive metrics, explain performance, and produce decision-ready reports.
AI reasons over the same governed definitions and metrics used by enterprise reporting.
Ontology and reusable knowledge encode how the company actually operates, measures performance, and interprets results.
Separated business knowledge, model access and presentation so the analytical layer can evolve with new agent capabilities.
Selected current engagements
Designing the analytical foundation across multiple operating entities and business systems, with emphasis on semantic consistency, master data, data quality, cross-system synchronization and governed reporting.
End-to-end analytics across NetSuite, cloud data platforms, semantic modeling and executive reporting — including P&L, budgets, forecasts, revenue, operations and management narratives.
Contributing to scalable workforce and payroll analytics across UKG Dimensions, event-driven ingestion, Azure/Synapse data platforms, semantic modeling and enterprise reporting.
Capabilities
Microsoft Fabric, Azure, lakehouse and warehouse design, integration architecture, APIs, ETL/ELT and event-driven systems.
Enterprise semantic models, Power BI, DAX, dimensional modeling, centralized business logic, KPI frameworks and performance optimization.
Natural-language analytics, business ontology, semantic grounding, MCP/tool integration, context engineering and AI analytical applications.
Master data, business definitions, security, RLS, lineage, cross-system reconciliation, compliance-oriented analytics and trusted metrics.
P&L, forecasting, budgeting, workforce, sales, operations and decision-support systems built with business leaders, not around them.
MCPs, reusable skills, AI-assisted development and agentic workflows applied to analysis, engineering, testing, documentation and delivery.
“The semantic layer is no longer just where dashboards get their metrics. It is where humans and AI learn what the business means.”
About
I started in data engineering and business intelligence, then moved progressively toward architecture, enterprise semantic modeling and decision systems. Today my work sits at the intersection of data platforms, business context and AI.
An Executive MBA complements my Computer Science background and helps me work comfortably across engineering, Finance, Operations and executive teams — translating business problems into technical systems that remain understandable, governed and useful.
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Business intelligence & data engineering
Architecture, enterprise analytics & consulting leadership
Executive MBA — Mediterranean School of Business
Semantic intelligence & AI-powered analytics
Open to the right challenge
Interested in senior architecture, principal analytics, semantic intelligence and AI/agentic analytics opportunities with ambitious data organizations.