Sr Principal Product Owner – Data Management & Integration Services

Are you ready to redefine how data becomes enterprise intelligence — and to own the integration backbone that lets AI act on it?
At Keurig Dr Pepper, we're building the future of data — one domain, one signal, one intelligent decision at a time. Great AI doesn't start at the model; it starts at the data and the seams between systems. Our strategy is to converge these patterns into one governed Enterprise Integration Gateway — standardize, secure, govern — so that trusted, catalog-governed data can be both created and consumed by AI: agents, models, and copilots operating in the flow of work.
We're looking for a product owner who can own both ends: the modern data platform that makes data AI-ready, and the enterprise integration gateway that lets AI discover, govern, and act on that data. If you thrive at the intersection of AI engineering, enterprise integration, and data operations — and you want to turn bleeding-edge technology into real business transformation — this is your moment.
Your Mission
As the Sr Principal Product Owner – Data Management & Integration Services, you will execute KDP's Data Mgmt and AI Data Readiness strategy for next-generation data platforms, and drive the AI integration strategy that optimizes for AI data creation and consumption. You will own the capabilities that acquire, move, standardize, and govern enterprise data — from raw ingestion through the Enterprise Integration Gateway (API management, event streaming/CDC, microservices, iPaaS, and agent/MCP patterns) to domain-based data ownership, medallion-architected pipelines, and AI-embedded DataOps. This role is central to KDP's Unified Architecture and to making our data — structured and unstructured — trusted, discoverable, and ready for an AI-augmented enterprise.
What You'll Do
AI Integration Strategy — One Front Door for AI (Emphasis Area)
• Drive the AI integration strategy that optimizes for AI data creation (AI-ready ingestion, enrichment, and pipeline generation) and AI data consumption (agents, models, apps, and copilots acting on trusted data).
• Own the roadmap for the Enterprise Integration Gateway — converging a fragmented estate of ETL, B2B/EDI, API/app, and file-transfer integrations into one governed, composable, enterprise-wide gateway that standardizes, secures, and governs how data and services cross every boundary.
• Establish modern integration patterns as the enterprise standard: API management, event streaming / CDC, microservices, iPaaS, and agent frameworks / MCP — enabling AI agents (autonomous and assisted, human-in-the-loop), models (reasoning over catalog-governed data), and copilots (in the flow of work via discoverable APIs).
• Champion an API-first, microservices strategy: API lifecycle management, REST API design, gateway architecture, event-driven patterns, and API standards (auth, versioning, rate limits, error contracts, observability, deprecation), leading the migration from legacy point-to-point patterns to reusable integration services.
AI Data Readiness & AI Engineering Enablement
• Deliver capabilities that make data AI-ready — unifying structured and unstructured data, and enabling reasoning over trusted, catalog-governed assets
• Execute AI-embedded, AI-augmented DataOps — automated governance, anomaly detection, and intelligent metadata discovery — treating AI as a force multiplier for pipeline creation, data management, and self-service (e.g., Databricks AI enablement such as Genie, AgentBricks, and Mosaic AI)
• Partner with platform/AI engineering to enable ML/feature workloads and AI consumption — Unity Catalog-governed models and feature stores, cataloged prompts and datasets for auditability, and discoverable APIs that put trusted data in the flow of work
Execution of Strategic Data Capabilities
• Deliver platform capabilities that support raw data ingestion, profiling, and domain-based ownership across the enterprise
• Operationalize medallion architecture (Bronze → Silver → Gold) to support scalable, governed data pipelines fed by enterprise integration flows
• Apply the enterprise decision framework (federate to prove value, migrate to optimize and govern) to balance speed-to-value with compute/storage efficiency
• Translate business needs into prioritized backlogs and sprint plans that accelerate AI enablement and data readiness
Domain Stewardship & Marketplace Partnership
• Enable domain stewards to manage and activate their data assets through platform capabilities and tooling
• Partner with the Enterprise Data Marketplace team to ensure seamless integration, lineage, and discoverability of curated, AI-ready data products
Stakeholder Engagement
• Collaborate with Enterprise AI Services, business units, data stewards, integration/trading partners, and technical teams to align on governance, access policies, connec