Staff Product Manager, Unistore (hybrid Tables)

Snowflake Snowflake · Data AI · WA-Bellevue, United States · Product Management

Staff Product Manager for Snowflake's Unistore (Hybrid Tables) product, focusing on the convergence of OLTP and analytical workloads. The role involves defining product strategy, roadmap, and go-to-market execution, with a significant emphasis on enabling AI-driven workflows and serving as the low-latency transactional backbone for agentic enterprise applications. Requires deep database systems experience and strong product management skills.

What you'd actually do

  1. Drive the Unistore product area end-to-end—including product strategy, roadmap prioritization, and go-to-market execution.
  2. Rally engineering and product leadership around a compelling 2-3 year vision for Unistore, identifying untapped market opportunities for the next frontier of hybrid data.
  3. Define and drive clear requirements for data movement, storage lifecycle, reliability, cost, and quality of service.
  4. Champion AI-driven workflows by defining how Unistore serves as the low-latency transactional backbone for agentic enterprise applications—ensuring our storage systems meet the speed, consistency, and reliability demands of real-time AI-driven workloads at scale.
  5. Lead cross-functional collaboration with marketing, sales, and solutions teams on positioning, enablement, and customer engagement.

Skills

Required

  • 8+ years of product management experience
  • strong track record of driving significant product areas through ambiguity and organizational complexity
  • deep background in database systems
  • Proven go-to-market and cross-functional experience working closely with sales and solutions teams on technical products
  • The ability to articulate a compelling multi-year product vision
  • hold your own in roadmap debates with senior engineering leaders
  • Strong communication and influence skills
  • ability to represent the product credibly to C-suite stakeholders
  • write persuasively
  • Demonstrated ownership and grit
  • taking responsibility when things aren’t going well
  • thriving in a startup-like environment within a larger organization

What the JD emphasized

  • AI-driven workflows
  • low-latency transactional backbone for agentic enterprise applications
  • real-time AI-driven workloads at scale