Principal Product Manager

SAP•Stanford, CA

18d•$198,200 - $420,000•Hybrid

About The Position

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.

Requirements

Extensive product management experience in data infrastructure, cloud platforms, or enterprise software with a track record of developing or shipping products customers love.
Hands-on familiarity with the modern data stack and the major platform players: Snowflake, Databricks, BigQuery, Microsoft Fabric, AWS data services. You should have strong, informed opinions about the ecosystem.
Deep understanding of data platforms: connectivity, sharing, governance, performance, security, scale, and where the industry is going next.
Working knowledge of the SAP portfolio and BDC. Familiarity with SAP data integration is a plus - strong outside-in product judgment matters more.
Real expertise with the technologies underneath the product: Apache Iceberg, Delta Lake, distributed systems, Kubernetes, Spark, and at least one systems language (Rust, Go, Java). You do not need to write it daily, but you need to reason about it.
A clear track record of enabling AI and ML workloads through better data foundations - not slideware but shipped product.
Proven ability to operate as the single product owner across multiple engineering teams and stakeholders, with the credibility to drive decisions.
First-principles product thinking.
Customer-facing scar tissue from real enterprise engagements - including the hard escalations - and a habit of turning that signal into product.
Engineering or technical consulting background. You can read the code when you need to.
Strategic clarity paired with a bias to ship. You are measured by adoption and outcomes, not roadmap slides.
Strong communicator. You can hold the room with executives, customers, and engineers — and tell each of them the same true thing.
Bachelor's degree in a relevant field; advanced degree a plus.

Nice To Haves

Familiarity with SAP data integration is a plus

Responsibilities

Set and own the end-to-end strategy and roadmap for BDC Connect from raw customer signal to shipped and adopted product. You are driving this together with your engineering counterparts.
Spend serious time with customers and partners. Be in the room for the hard escalations. Your roadmap should reflect what you have heard and seen, not only what you have read.
Be the deepest product expert on the personas you serve: data engineers, platform owners, AI builders. Solve their actual pains and jobs-to-be-done.
Treat every integration as leverage, not a one-off. The right architecture compounds as each new partner makes the next one easier and the platform more valuable.
Operate with a product-led growth mindset. Instrument everything. Let usage and customer outcomes not opinion settle the product direction.
Hold a sharp, defensible point of view on what AI-native data integration looks like and then ship it.
Pick a small set of metrics that matter. Move them. Be honest about what is working and what is not.
Customers and partners come first. SAP leadership, the AI organization, LoBs, and the field come next and they get the same clarity, care, and pace you bring to customers.
Communicate vision, strategy, and progress with precision. Set expectations early. Surface risk before it becomes news.
Drive alignment across multiple engineering stakeholders that your roadmap and execution success depends on. Identify and resolve bottlenecks to get the product moving.
Represent the product externally in customer meetings, industry events, executive briefings.
Stay sharp on the data and AI landscape. Know what Snowflake, Databricks, and the hyperscalers are doing.
Improve how the team works. Cut what does not create customer value. Build the muscle to ship faster without losing quality.
Create the kind of team environment strong PMs want to join: high standards, real ownership, fast feedback, no politics.