Principal Product Manager
Principal Product Manager owning strategy, roadmap, and GM responsibilities for Snowflake's Snowpark platform. Drive 0→1 expansion into unstructured, multimodal, and agentic AI data processing while leading growth of Python/Java/Scala distributed workloads. Requires 8+ years PM experience, deep Python/distributed systems expertise, and AI-native fluency.
About the job
Responsibilities
- Define the multi-year strategy and roadmap for Snowpark as the standard for distributed Python, Java, and Scala processing on the data platform.
- Drive expansion into unstructured/multimodal data processing and agentic, Python-based data engineering to open new markets.
- Own ML and AI inference workloads, Python expansion areas, batch pipelines, and core Snowpark surface including execution engine, security, and governance.
- Act as GM for the product: partner with Sales, Sales Engineering, and Marketing to accelerate adoption and growth.
- Collaborate with engineering, ecosystem, and orchestration teams (e.g., Airflow integrations) to define the end-to-end Snowpark experience.
- Serve as the definitive internal and external voice on Snowpark for engineering, SEs, and customers.
Requirements
- 8+ years of Product Management experience in developer platforms, data infrastructure, or cloud infrastructure.
- Deep familiarity with the Python ecosystem and distributed data processing at scale.
- Comfortable debating technical tradeoffs with senior engineers; ideally hands-on experience as a Python developer, data scientist, or data engineer.
- Proven track record of taking products 0→1 and/or driving high growth on owned products.
- Familiarity with modern AI tooling for data platforms (e.g., MCP, agentic workflows, ML inference) and how they reshape data processing.
- Data-driven with strong analytical rigor; comfortable using metrics and AI-assisted analysis to prioritize under ambiguity.
- High ownership: resilient, low-ego, diplomatic, able to have candid conversations while aligning cross-functional partners.
Nice-to-Haves
- 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.
- Background leading or mentoring other product managers.
Skills
Product Management, Python, Distributed Data Processing, Ml Inference, AI Workflows, Data Infrastructure, Cloud Infrastructure, Agentic AI, Unstructured Data, Multimodal Data, Snowpark, Go-To-Market
Similar jobs
Product Management jobs
Headway
United States
Own the strategy and execution of Headway’s ML-powered patient-provider search, retrieval, and ranking systems. The role requires 10+ years of product management experience, shipped ranking or relevance systems, strong technical fluency in ML evaluation, and executive leadership.
Chime
San Francisco, CA
Leads the end-to-end acquisition and conversion strategy for Chime’s lending portfolio, spanning loans, credit cards, and lines of credit. Requires 11+ years of consumer product leadership and proven top-of-funnel lending experience with measurable growth, conversion, and CAC results.
Crusoe
San Francisco, CAOwn the multi-year vision, architecture, vendor strategy, and economics of Crusoe’s hyperscale storage foundation supporting AI workloads. The role requires 8+ years of technical product or infrastructure experience, deep storage expertise, and the ability to partner with senior engineering leadership.
Crusoe
Sunnyvale, CALeads the multi-year product vision, architecture, vendor strategy, and economics for Crusoe’s AI networking foundation. Requires 8+ years of technical product management or infrastructure engineering experience, deep networking expertise, and hands-on experience with RDMA and GPU cluster networking.
Headway
San Francisco, CAOwn the foundational data products that segment patients, measure cost of care, and translate outcomes into auditable payer-facing products. The role requires deep technical fluency, complex data infrastructure product ownership, and cross-functional leadership across engineering, clinical, and commercial teams.