OverviewMicrosoft's Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture.
Within Azure Data, the messaging and real-time analytics team provides comprehensive solutions and a robust platform that enables users to ingest high granularity signals (real-time & observability) and complex data, converting those into a competitive advantage in real-time for both end users and modern applications.
IQ Team - Ontology & Semantic Layer: We are building the operational brain for organizations to run their agents and business on. At its core, we build the semantic backbone that gives AI agents the context they need to reason about business. The IQ team helps organizations define a unified ontology which is a living, structured description of how their business works: its entities, relationships, processes, and rules.
By bridging raw data and business meaning, we enable AI agents to understand not just what the data says, but what it means by powering grounded, trustworthy, and actionable intelligence at scale.
Responsibilities- Own a customer problem space within the ontology as the semantic operational context for organizations. This includes customer problem definition and PRD through roadmap execution with engineering, and launch and landing with customers and field.
- Drive AI agent grounding scenarios by leveraging ontology to give agents structured business context, improving reasoning accuracy, reducing hallucinations, and enabling trusted, autonomous decision-making.
- Translate customer needs into ontology platform features and adoption guidance, defining a phased path from raw data to a unified semantic layer that amplifies existing analytics investments and unlocks operational agent scenarios.
- Influence ontology technical architecture and long-term platform strategy in close collaboration with engineering, design and data science.
- Drive strategic partnerships and cross-org alignment to unlock new ontology scenarios, amplify impact, and deliver a cohesive semantic and AI stack across Fabric.
- Define success metrics and SLT-level KPIs for ontology feature adoption, leading initiatives that deliver measurable customer impact and platform growth.
- Embody our culture and values.
QualificationsRequired Qualifications:- Bachelor's Degree AND 5+ years experience in product/service/project/program management or software development
- OR equivalent experience.
Other Requirements:Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check:
- This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications:- 7+ years of experience in product management, or related roles in the AI and data and analytics domain. Proven track record of leading, shipping and delivering complex and innovative Data & AI solutions that create value for customers and stakeholders, using Microsoft AI or similar technologies.
- Deep data modeling & semantic systems: Experience across relational, dimensional, semantic, ontology, or graph models, with hands-on experience working with business domains (entities, relationships, metrics, events, temporal context).
- AI + Data Platform Fluency: Deep understanding of enterprise data platforms (warehouse, Lakehouse, semantic layers, metadata systems) and how to ground AI/agents in business semantics to deliver accurate, trustworthy outcomes.
- End-to-end product execution: Proven ability to lead the full product lifecycle from market insight and ideation through delivery and adoption with rigor in prioritization, quality, compliance, and differentiation.
- Customer-centric problem solving: Ability to translate ambiguous customer scenarios into clear modeling requirements, technical tradeoffs, and phased adoption journeys that drive measurable customer value.
- Metadata, governance, and platform depth: Experience with metadata systems, lineage, governance, schema evolution, and data quality, with a pragmatic approach to building scalable, enterprise-ready platforms.
- Cross-org leadership and external engagement: Ability to drive alignment across engineering, research, and platform teams, while engaging customers, partners, and ecosystem players to validate product-market fit and shape the category narrative.
#azdat #azuredata #FabricIQ #Ontology #RealTimeIntelligence #AIProduct Management IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
