Group Product Manager, Enterprise Data

Intuit is reimagining how enterprise data is discovered, understood, governed, and consumed in an agent-first world. Historically, data platforms have optimized for expert users navigating schemas, tools, pipelines, and access processes. As AI agents become a primary interface for analytics, product experiences, decisioning, and automation, those legacy workflows are no longer sufficient. Our opportunity is to redesign the enterprise data experience from the ground up.

Within Data Foundations, we are building an enterprise context layer that gives every application, user, and AI agent access to clean, connected, governed business context without requiring them to understand the underlying complexity of where data lives or how it is modeled. At the center of this strategy is the Business Object Model, which establishes canonical definitions for Intuit’s most important business concepts and relationships.

Around that foundation, we are creating reusable agent context, trusted and quality-controlled data, semantic relationships, metadata, lineage, and policy-aware access patterns that can be consumed consistently across Intuit.

Our ambition is to make the default experience. The Group Product Manager for Enterprise Data, Context Layer & Agent-First Data Consumption will lead this transformation. This leader will define how Intuit builds the context layer that sits between foundational enterprise data and the agents, applications, analysts, and customer experiences that depend on it. The role spans product strategy for the Business Object Model, agent-ready context, governed consumption, self-service discovery and access, and the paved paths that make these capabilities the easiest and fastest way to build at Intuit.

The opportunity is larger than modernizing a data platform. It is to establish the enterprise context architecture for Intuit’s agentic future.

• Define the multi-year product vision, strategy, and roadmap for Intuit’s Enterprise Context Layer and Agent-First Data Consumption capabilities.
• Lead transformation of agent led governance, data access, data processing and create new data science paved paths
• Lead the transformation from legacy, human-centric data workflows toward agent-first, intent-driven, self-service consumption experiences.
• Establish the product strategy for the enterprise context layer that provides applications and AI agents with trusted business meaning, relationships, metadata, lineage, quality, and policy-aware access.
• Partner with engineering and architecture to make clean, connected enterprise data available through reusable, scalable interfaces designed for both human and machine consumers.
• Define how reusable agent contextis created, governed, composed, retrieved, and shared across multiple AI agents and product experiences.
• Establish product requirements for agent-consumable semantics, relationships, metadata, lineage, data quality, and policy signals.
• Reimagine existing discovery, access, reconciliation, onboarding, and integration workflows to remove unnecessary human intervention and engineering dependency.
• Lead the evolution from manual and ticket-driven access processes toward fine-grained, automated, policy-aware access control.
• Partner across privacy, security, legal, data governance, and engineering to embed authorization, purpose, consent, and permitted-use policies directly into the context and consumption experience.
• Establish clean-data expectations and product mechanisms for quality, certification, freshness, provenance, and trust within the context layer.
• Translate complex customer requirements, business semantics, technical constraints, and governance requirements into reusable platform capabilities.
• Build deep partnerships with product,…