Principal Product Manager - Snowpark

1 мес. назад

264k–379.5k USD / yearUSALead

pythonjavascala

Leading the strategy, growth, and go-to-market for Snowpark, a fast-growing product enabling distributed workloads on 's platform.

Обязанности

Snowpark is how developers run distributed Python, Java, and Scala workloads directly on the platform — securely, at scale, and without moving data. It is one of '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.

Будет плюсом

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.
is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and .
How do you want to make your impact?
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Другое

At , we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At , your role isn't just to execute a function, but to help redefine the future of how work gets done.
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 .
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.