Staff Product Manager, SAPActive$172K

Databricks
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The opportunity

SAP will serve as the foundation for Databricks' core finance processes, including Record-to-Report, Source-to-Pay, and Order-to-Cash. As the SAP Product Manager, you will shape how Finance users interact with these processes by building an intelligent, AI-powered agentic layer on top of SAP.

What you'll do

  • Own the SAP & Intelligent Automation Strategy: Lead the product strategy and roadmap for Databricks' SAP platform, ensuring it serves as the foundation for scalable, best-in-class finance operations. Drive SAP implementations, platform evolution, and business process transformation while defining the automation roadmap that leverages AI and agentic workflows to simplify user experiences, reduce manual effort, and improve operational efficiency.

  • Lead the AI & Agentic Layer: Design, build, and deploy intelligent agentic workflows on top of SAP, partnering with engineering and data teams on the orchestration, retrieval, and guardrail patterns that make agents safe to act on financial and procurement data.

  • Unify SAP Data in the Lakehouse: Own the product requirements for getting SAP data into Databricks, including ingestion, semantic and master data modeling, lineage, and governance, so that AI, analytics, and downstream applications work from one trusted definition of the business.

  • Serve as Product Owner in Delivery: Own the backlog and acceptance criteria, run prioritization and release planning with internal and partner engineering teams, and drive readiness, cutover, adoption, and change management for what you ship.

  • Domain Leadership: Act as the primary product leader for core SAP domain, and as the connective tissue across the SAP ecosystem, including BTP, Integration Suite, and the non-SAP systems around it.

  • Execute and Measure: Define success metrics (process cycle time, touchless transaction rate, automation accuracy, adoption, close efficiency, cost-to-serve) and use data-driven insights to guide rapid iteration.

What they're looking for

  • Experience developing custom applications or automation layers on data: platforms (such as Databricks) that extend or sit alongside SAP.
  • Familiarity with the SAP AI and extension stack, including BTP, and AI Core,: and a clear point of view on build-versus-adopt tradeoffs against a Databricks native approach.
  • Hands-on knowledge of SAP integration surfaces and their limitations,: including OData and REST APIs, CDS views and Datasphere.