Principal Product Manager
SAP · Palo Alto, CA
- On site
- Full-time
- $309,100 / year
- Palo Alto, CA
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Principal Product Manager
SAP · Palo Alto, CA
Riley Chen
Hiring Manager · h•••••@jobs.sap.com
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Hi Riley — I came across the Principal Product Manager opening and wanted to reach out directly. I've spent the last few years doing exactly this kind of work, and SAP stood out because…
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Not recommended alone — most applicants never hear back.
Job highlights
- Own product strategy and roadmap for BDC Connect.
- Drive bi-directional, semantically rich data sharing.
- Engage deeply with customers and partners.
- Lead product development with AI-native integration.
- Collaborate across engineering and stakeholders.
About the role
Role Summary
Enterprise AI is only as good as the data it can reach. Today, that data is fragmented across SAP, hyperscalers, lakehouses, and SaaS - locked behind connectors, copies, and brittle pipelines. We are building the opposite: a single, governed, zero-copy fabric that makes every customer's data wherever it lives usable for analytics, applications, and AI agents.You will own the product for BDC Connect: the strategic surface where SAP Business Data Cloud meets AWS, Databricks, Google Cloud, Microsoft Fabric, and Snowflake. Bi-directional, semantically rich, governed data sharing at performance and scale. This is one of the highest-leverage product roles at SAP. Get it right, and BDC becomes the gravity well for enterprise data.
We are looking for a product leader with deep technical taste, strong opinions on what great looks like. You will set the strategy, drive the roadmap, and be accountable for execution and outcomes.
What You'll Do
- Own the Product: Set and own the end-to-end strategy and roadmap for BDC Connect from raw customer signal to shipped and adopted product, in collaboration with engineering counterparts.
- Spend significant time with customers and partners, actively participating in difficult escalations. Your roadmap should reflect direct customer feedback and observations.
- Become the foremost expert on the personas you serve: data engineers, platform owners, and AI builders, addressing their actual pain points and jobs-to-be-done.
- Treat every integration as a strategic advantage, ensuring the architecture compounds value as new partners are added, making the platform more robust and useful.
- Operate with a product-led growth mindset, instrumenting everything to allow usage and customer outcomes to guide product direction rather than opinion.
- Build and Ship: Develop and execute a clear vision for AI-native data integration, focusing on a few key metrics that drive adoption and success. Be transparent about what is and isn't working.
- Drive Alignment: Prioritize customers and partners, ensuring SAP leadership, the AI organization, LoBs, and the field receive clear, consistent communication regarding vision, strategy, and progress.
- Proactively surface risks and potential issues to relevant stakeholders.
- Foster alignment across multiple engineering teams, identifying and resolving bottlenecks to ensure successful product execution.
- Represent the product externally in customer meetings, industry events, and executive briefings.
- Raise the Bar: Stay informed on the latest developments in the data and AI landscape, including competitor activities from Snowflake, Databricks, and hyperscalers.
- Continuously improve team processes, eliminating activities that do not create customer value and enhancing the ability to ship faster without compromising quality.
- Cultivate a high-performing team environment characterized by high standards, genuine ownership, rapid feedback, and minimal politics, attracting top product management talent.
What You Bring
- Extensive product management experience in data infrastructure, cloud platforms, or enterprise software with a proven track record of developing or shipping customer-loved products.
- Hands-on familiarity with the modern data stack and major platform players such as Snowflake, Databricks, BigQuery, Microsoft Fabric, and AWS data services, coupled with strong, informed opinions on the ecosystem.
- Deep understanding of data platforms, including connectivity, sharing, governance, performance, security, and scalability, with foresight into industry trends.
- Working knowledge of the SAP portfolio and BDC; familiarity with SAP data integration is a plus, but strong outside-in product judgment is more critical.
- Expertise with underlying technologies such as Apache Iceberg, Delta Lake, distributed systems, Kubernetes, Spark, and at least one systems language (Rust, Go, Java)—sufficient to reason about them even if not coding daily.
- A clear track record of enabling AI and ML workloads through robust data foundations, demonstrated by shipped products, not just concepts.
- Proven ability to act as the sole product owner across multiple engineering teams and stakeholders, with the credibility to drive key decisions.
- First-principles product thinking and practical experience from real enterprise engagements, including handling difficult escalations and translating that signal into product improvements.
- An engineering or technical consulting background that enables you to understand code when necessary.
- Strategic clarity combined with a bias for action and shipping; success measured by adoption and outcomes, not just roadmap presentations.
- Strong communication skills, capable of engaging effectively with executives, customers, and engineers, delivering consistent and truthful information to each audience.
- Bachelor's degree in a relevant field; an advanced degree is a plus.
Key skills/competency
- Product Management
- Data Infrastructure
- Cloud Platforms
- Enterprise Software
- Data Strategy
- AI/ML Enablement
- Product Roadmapping
- Customer Engagement
- Technical Acumen
- Cross-functional Leadership
Skills & topics
- Principal Product Manager
- Product Management
- Enterprise AI
- Data Infrastructure
- Cloud Platforms
- Data Strategy
- Roadmap
- Customer Engagement
- Snowflake
- Databricks
- SAP
- BDC Connect
- Data Sharing
- Governance
- Apache Iceberg
- Distributed Systems
- Kubernetes
- Spark
- Rust
- Go
- Java
- AWS
- Google Cloud
- Microsoft Fabric
How to get hired
- Tailor your resume: Highlight experience in data infrastructure, cloud platforms, and enterprise software, emphasizing product shipping and customer love.
- Showcase technical depth: Detail your familiarity with modern data stacks (Snowflake, Databricks) and underlying technologies (Apache Iceberg, Spark, distributed systems).
- Quantify achievements: Provide evidence of enabling AI/ML through data foundations, focusing on adoption and outcomes, not just roadmaps.
- Demonstrate leadership: Highlight your ability to drive decisions across multiple engineering teams and communicate vision effectively to diverse stakeholders.
- Prepare for technical discussions: Be ready to discuss your opinions on the data ecosystem and reason about complex technical systems.
Technical preparation
Deep dive into modern data stack platforms.,Study distributed systems and data governance principles.,Understand Apache Iceberg and Delta Lake architectures.,Review SAP's Business Data Cloud (BDC) capabilities.
Behavioral questions
Describe a time you owned a complex product roadmap.,How do you handle escalations with difficult customers?,Share an example of driving alignment across teams.,How do you stay sharp on industry trends?
Prefer to apply the usual way?
Not recommended alone — most applicants never hear back. Email the hiring manager first.
Frequently asked questions
- What specific SAP products or platforms are relevant for a Principal Product Manager at SAP focusing on BDC Connect?
- For this Principal Product Manager role focusing on BDC Connect, familiarity with the SAP Business Data Cloud (BDC) is important. The role also involves integrating with major cloud platforms and data players like AWS, Databricks, Google Cloud, Microsoft Fabric, and Snowflake. Understanding the broader SAP portfolio is beneficial, though deep outside-in product judgment is prioritized.
- How does SAP view the use of AI in its recruitment process for a Principal Product Manager?
- SAP utilizes AI responsibly in its recruitment process. Candidates are encouraged to review SAP's Guidelines for Ethical Usage of AI in the Recruiting Process, as adherence to these guidelines is critical and any violations may lead to disqualification.
- What kind of technical background is expected for a Principal Product Manager in Enterprise AI at SAP?
- The Principal Product Manager role requires deep technical taste. This includes hands-on familiarity with the modern data stack and platforms like Snowflake and Databricks. Expertise in underlying technologies like Apache Iceberg, Delta Lake, distributed systems, Kubernetes, and Spark is essential, along with the ability to reason about them. An engineering or technical consulting background is highly valued.
- How does SAP ensure inclusion and support for employees, particularly in roles like Principal Product Manager?
- SAP fosters a culture of inclusion, prioritizing employee wellbeing and offering flexible working models. They believe diversity strengthens the company and invest in employee development. SAP is committed to Equal Employment Opportunity and provides accessibility accommodations. They also have specific programs like the SAP Employee Referral Program for internal referrals.
- What is the compensation range for a Principal Product Manager at SAP?
- The targeted annual compensation range for this Principal Product Manager position at SAP is between $198,200 and $420,000 USD. The final offer will depend on factors such as education, skills, experience, role scope, and location.
- What are the key responsibilities for the Principal Product Manager, BDC Connect role at SAP?
- The Principal Product Manager will own the strategy and roadmap for BDC Connect, focusing on bi-directional, semantically rich, governed data sharing between SAP Business Data Cloud and major cloud providers. Key responsibilities include deep customer engagement, technical product expertise, driving adoption, and aligning multiple engineering teams.
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