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Staff Product Manager, Serverless Workspaces

Databricks· Engineering
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Hybrid (San Francisco, CA / Seattle, WA)$181.7k - $249.8kfull-timePosted 8mo ago

About the role

Product role focused on building a serverless workspace platform to simplify onboarding, govern governance, and unify data access within Databricks’ cloud infrastructure offerings.

Responsibilities

  • Drive the transition to Serverless: lead the strategy to unify onboarding to serverless and classic workspaces and drive 10X usage of serverless in the next year
  • Democratize Workspace Creation: design and ship flows that allow users to spin up workspaces instantly with little friction while maintaining governance guardrails and policies
  • Redefine the Getting Started experience: lower the barrier to entry by removing the requirement for customers to manage detailed cloud infrastructure configurations, with opt-in advanced controls
  • Solve Workspace Proliferation: define tools and policies that allow Admins to govern increased workspace counts across the enterprise
  • Unify the Data Estate: collaborate with Unity Catalog and Identity teams to ensure serverless environments integrate with existing data and security models

Qualifications

  • 7+ years of experience as a Product Manager working on cloud infrastructure, developer platforms, or SaaS foundations
  • Technical depth in Cloud Infrastructure: familiarity with AWS, Azure, or GCP resource management (e.g. networking, compute, identity) and abstraction for end-users
  • Proven track record of simplifying complex technical workflows into consumer-grade experiences
  • Data-driven mindset with experience defining and tracking KPIs (e.g., Time to First Workspace, Serverless Adoption Rate)

Skills

Required:Product managementCloud infrastructureData-driven decision making

Benefits

  • Benefits details available on region-specific page (link provided in job description)
Last updated Sep 10, 2026. Interested? Apply on the company site.

About Databricks

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Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

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