Principal Product Manager - Snowpark

Snowpark is how developers run distributed Python, Java, and Scala workloads directly on the Snowflake platform - securely, at scale, and without moving data. It is one of Snowflake's most differentiated and fastest-growing products, and as workloads become agent-driven - where Python is the default - its growth is only accelerating.

Having expanded from structured data into semi-structured and ETL workloads, Snowpark is now entering its most exciting phase: unstructured, multimodal, and agentic AI data processing.

We are looking for a Principal Product Manager to own Snowpark and lead this next chapter. This is a general-manager-style role: you will own the strategy, growth, and go-to-market for a critical product line, acting as an entrepreneur with the autonomy to propose and launch multiple 0→1 bets on top of an already highly successful product.

You will be the most senior PM on the product, with a clear path to lead the Snowpark PM team as you demonstrate impact.

- Define the Mission: Own the end-to-end, multi-year strategy and roadmap for Snowpark as the standard for distributed Python, Java, and Scala processing on the data platform.

- Lead the 0→1: Drive the expansion into unstructured/multimodal data processing and agentic, Python-based data engineering - the greenfield bets that open new markets for Snowflake.

- Own the Platform: Own ML and AI inference workloads, Python expansion areas, batch pipelines, and the core Snowpark surface - execution engine, security, and governance.

- Drive Go-To-Market: Act as a GM for the product, partnering with Sales, Sales Engineering, and Marketing to accelerate adoption and growth.

- Collaborate Across Boundaries: Partner with engineering, ecosystem, and orchestration teams (e.g., Airflow integrations) to define the end-to-end Snowpark experience.

- Be the Go-To Expert: Become the definitive voice on Snowpark - internally for engineering and SEs, and externally for customers.

- 8+ years of Product Management experience in developer platforms, data infrastructure, or cloud infrastructure.

- Technical Robustness: Deep familiarity with the Python ecosystem and distributed data processing at scale. You are comfortable debating technical tradeoffs with senior engineers, ideally from hands-on experience as a Python developer, data scientist, or data engineer.

- A Growth Mindset: A proven track record of taking products 0→1 and/or driving high growth on something you personally owned.

- AI-Native Fluency: Familiarity with modern AI tooling for data platforms (e.g., MCP, agentic workflows, ML inference) and how they reshape data processing.

- Analytical Rigor: Data-driven and comfortable using metrics and AI-assisted analysis to hyper-prioritize and iterate under ambiguity.

- High Ownership: Resilient, low-ego, and diplomatic - able to have candid, tough conversations while keeping cross-functional partners aligned.

- Experience at a cloud platform provider (serverless/data processing), an open-source Python ecosystem company (e.g., Ray/AnyScale), a streaming platform (e.g., Flink/Confluent), or a PyData-space startup.

- Prior experience with unstructured or multimodal data processing.

- GM-style ownership of a product line, including go-to-market and business outcomes.

- A background of leading or mentoring other product managers.