Harry Arce
Apps, Data & AI, Senior Digital Technical Specialist
San José, Costa Rica
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Harry Arce is a technology leader and AI strategist at Microsoft who helps organizations transform data into competitive advantage. With more than two decades of experience spanning enterprise architecture, data platforms, cloud transformation, and artificial intelligence, he bridges the gap between emerging technology and real-world business outcomes.
Before joining Microsoft, Harry spent over 18 years at Intel driving large-scale digital transformation initiatives and modernizing enterprise data ecosystems. Today, he partners with customers across healthcare, financial services, insurance, and other regulated industries to accelerate innovation through Data, AI, and agentic applications.
Recognized for his expertise in cloud architecture, AI governance, and enterprise-scale modernization, Harry is passionate about helping organizations safely adopt the next generation of AI while building secure, scalable, and responsible technology foundations. Fluent in English and Spanish, he combines deep technical expertise with a consultative approach that empowers organizations to innovate with confidence.
Harry Arce is a distinguished Senior Digital Technical Specialist at Microsoft, renowned for his extensive expertise in cloud data architecture, artificial intelligence and project management. With an impressive tenure of over 18 years at Intel Corporation, Harry was instrumental in spearheading digital transformation initiatives, driving innovation, and enhancing operational efficiency through the deployment of advanced data architectures and AI/ML strategies.
In his current role at Microsoft, Harry excels in the realm of Data, AI & Apps Innovation, where he leverages his profound knowledge to assist businesses in harnessing the power of data for informed decision-making and achieving comprehensive digital transformation. His proficiency in both Spanish and English enables him to effectively communicate and collaborate in diverse environments.
Harry's commitment to excellence is further demonstrated by his numerous certifications in Azure, underscoring his dedication to delivering high-quality, scalable technology solutions that meet the evolving needs of modern enterprises
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Revolutionize Your Data Estate: Mastering Microsoft Fabric with Data Mesh and Medallion Architecture
In this session, we will explore two complementary approaches to building a robust and solid data estate on top of a unified and intelligent data platform like Microsoft Fabric: the vertical approach through data mesh and the horizontal approach through medallion architecture.
The vertical approach explains how data mesh democratizes and delegates access to Microsoft Fabric. By decentralizing data ownership and promoting domain-oriented management, each domain handles its own data products. This empowers teams, fosters innovation, and breaks down data silos, enhancing accessibility and cross-functional collaboration for better decision-making and faster insights.
The horizontal approach details implementing a new and extended version of medallion architecture in Microsoft Fabric using lakehouse, warehouse and eventhouse with data engineering tools. This method organizes data into bronze (raw), silver (cleaned and enriched), and gold (business-ready) layers, ensuring quality and accessibility at each stage. Structuring data this way streamlines processing, improves governance, and enhances analytics capabilities.
This session will explain how leveraging data mesh and medallion architecture increases the likelihood of success when designing a data architecture in Microsoft Fabric. Attendees will gain invaluable insights and practical strategies to enhance their data initiatives, drive organizational growth, and end up with strong architectural designs and patterns built on an open and governed data platform to meet the demands of modern analytics and AI needs.
One Endpoint to Rule Them All: Token Budgets, Guardrails, and Failover for Enterprise AI at Scale
It always demos beautifully. A developer drops a model endpoint and an API key into a .env file, the AI dazzles the room, everyone claps. Then the clapping stops and the bill arrives.
A cheaper, smarter model ships next quarter — but yours is welded into forty codebases. Ten teams want in. Finance wants to know who torched $40k in tokens last month. Security finds your key in a public repo. One region throttles at 9am and your flagship feature goes dark. Your dazzling pilot just became the thing nobody wants to own. This is where most enterprise AI quietly dies.
It doesn't have to. This session is the architecture that drags AI from demo to prime time — model-agnostic, governed, pro-code — with an AI Gateway (Azure API Management) as the one chokepoint every model call flows through.
Here's the heresy that saves you: stop coupling your code to a model. When every app and agent calls one stable endpoint, you swap Azure OpenAI for a Foundry model for a third party, A/B them in production, and fail over between them — without touching a single line of application code.
And the gateway hands you the three things every pilot is missing: secure (secret less identity, content-safety guardrails, full audit), scalable (per-team token budgets, semantic caching, onboard a new team in an afternoon), and resilient (load balancing and automatic failover across backends).
You'll leave with a pilot-to-production blueprint — not a hello-world you'll rip out the month after.
Fabric Artifacts as Code: Engineering Governed, Agentic Fabric Automation for SaaS Analytics
In a single-tenant shop, a clumsy semantic model is an annoyance. In a SaaS ISV with thousands of customers on shared Fabric capacity, it's a defect replicated thousands of times — opaque field names degrading Copilot, missing lineage breaking trust, a silent DAX bug shipping wrong numbers to every tenant, one runaway Spark job throttling them all. At ISV scale, manual data engineering doesn't add up — it multiplies.
This is the data-platform architecture that breaks that curve. We treat Fabric artifacts as source code — TMDL/TMSL/PBIR (the same tabular semantics as SQL Server Analysis Services) round-tripped through deterministic, testable cores — and automate the lifecycle end to end: Discover → Author → Audit → Modify → Publish → Govern, across a Lakehouse/Warehouse estate fed by Dataflows Gen2 and Data Factory.
Two pillars carry it. MCP: one server, ~35 typed tools mirroring a single service layer 1:1, so agents and humans share one capability set. Skills: versioned, governed capability packs (modeling, DAX, accessibility/BPA audits, domain-grounded metadata) that encode expert practice as reusable units — your best practices in tooling, not in three people's heads.
Then the parts that matter at scale: lineage and cataloging beyond basic Purview, data-quality gates, capacity governance, multi-tenant isolation, secret less identity, and "deterministic by default, agentic by preference" so a write to a customer's model is always safe.
Building Medallion Architectures in Microsoft Fabric Using Lakehouse, Warehouse, and Eventhouse
Overview: This workshop will explore constructing an extended medallion architecture within Microsoft Fabric, utilizing the latest features in lakehouse, warehouse, and eventhouse. Medallion architecture organizes data into bronze (raw), silver (cleaned and enriched), and gold (business-ready) layers, ensuring data quality and accessibility at each stage. This structured approach streamlines data processing, improves governance, and enhances analytics capabilities.
Proposal: Join us for a comprehensive full-day workshop designed to equip participants with the knowledge and skills to build a robust medallion architecture in Microsoft Fabric. The workshop will be divided into interactive sessions, each focusing on different aspects of the architecture and its implementation.
-Morning Session: Introduction to medallion architecture and exploring the latest features of Microsoft lakehouse.
-Midday Session: Implementing warehouse solutions and hands-on exercises to set up and configure the architecture.
-Afternoon Session: Integrating eventhouse concepts and exploring advanced features and best practices.
By the end of the workshop, attendees will have practical strategies to build strong architectural designs and patterns on an open and governed data platform, meeting the demands of modern analytics and AI needs.
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