Staff Product Manager, SAP

Databricks•Mountain View, CA

4d•$172,200 - $236,850

About The Position

We're looking for a Product Manager to lead the strategy, implementation, and evolution of our SAP platform. In this role, you'll define the product vision for SAP as the foundation of Finance operations while building the intelligent automation layer that transforms manual, transaction-heavy processes into streamlined, AI-powered workflows. Working closely with Finance and Engineering, you'll shape the future of finance operations by combining the strength of SAP with agentic AI to deliver a simpler, more automated, and more intelligent experience for Finance users. 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. Rather than navigating multiple systems and performing manual tasks, Finance teams will rely on AI-driven workflows that automate routine work, surface the right insights, and guide users through exceptions and approvals. Your mission is to combine the strength of SAP with the power of the Databricks AI to create a modern, highly automated finance experience that enables the business to scale.

Requirements

7+ years of product management or product ownership experience, with a proven track record leading enterprise ERP initiatives at scale, including at least one large SAP implementation, S/4HANA migration, or major module rollout.
Specialist Domain Expertise: Deep functional background in SAP and the business processes it runs, with concrete experience in one or more of record-to-report, source-to-pay, or order-to-cash, and working fluency in the adjacent areas and in master data governance.
Agentic Automation & Advanced AI: Hands-on experience or a strong technical understanding of agentic automation, LLM orchestration, retrieval-augmented generation, and evaluation, with clear judgment about where AI belongs in a controlled, auditable ERP process and where it does not.
Data Fluency: Strong understanding of building on modern data platforms, including SAP data extraction and modeling, pipelines, semantic layers, and the practical work of making ERP data usable for analytics and AI.
Strategic & Product Thought Leadership: Demonstrated ability to own a product domain end-to-end, linking automation outcomes directly to finance and operations goals rather than to feature delivery.
Governance Rigor: Working knowledge of SAP authorizations, SoD, SOX and audit requirements, and modern enterprise governance practice, and the ability to design automation that satisfies them.
Ambiguity Champion: Highly comfortable leading through extreme ambiguity, managing complex stakeholder landscapes across business and IT, and collaborating directly with engineering pods to build applications from scratch.

Nice To Haves

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.

Responsibilities

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.
Influence and Collaborate: Align Finance, Procurement, Enterprise Architecture, Security, and senior leadership around the automated product vision, and evangelize the roadmap in company-wide productivity and AI discussions.