GAQ126R40
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.
The OpportunitySAP 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.
The impact you will have:
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.
What we look for:
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.
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.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Skills Required
- 7+ years of product management or product ownership experience
- Proven track record leading enterprise ERP initiatives at scale, including at least one large SAP implementation or S/4HANA migration or major module rollout
- Deep functional background in SAP and related business processes (record-to-report, source-to-pay, order-to-cash)
- Working fluency in master data governance and adjacent areas
- Hands-on experience or strong technical understanding of agentic automation, LLM orchestration, retrieval-augmented generation, and evaluation
- Strong data fluency with modern data platforms, including SAP data extraction, modeling, pipelines, and semantic layers
- Working knowledge of SAP authorizations, Segregation of Duties (SoD), SOX and audit requirements
- Experience acting as product owner: backlog ownership, acceptance criteria, prioritization, release planning, and change management
- Comfort leading through ambiguity and managing complex stakeholder landscapes across business and IT
- Experience developing custom applications or automation layers on data platforms (such as Databricks)
- Familiarity with the SAP AI and extension stack (including BTP and AI Core) and build-vs-adopt tradeoffs
- Hands-on knowledge of SAP integration surfaces and limitations (OData, REST APIs, CDS views, Datasphere)
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants are a meaningful part of offers, and periodic tender opportunities and secondary options have made private equity more tangible for many employees. This perceived upside contributes to strong total-compensation sentiment in key roles.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is paired with mental‑health resources and wellness reimbursements, indicating a robust health package. Multiple summaries highlight broad coverage that employees can practically use.
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Leave & Time Off Breadth — Generous PTO, paid holidays/sick time, and fully paid parental leave are frequently described, with hybrid/remote flexibility common in the U.S. These policies expand time‑off accessibility across different life stages.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
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