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HomeJobsOperationsStaff Product Manager, Serverless Workspaces
D

Staff Product Manager, Serverless Workspaces

Databricks• 25 days ago•via greenhouse:databricks
Full-time Fully remote Salary not disclosed

Job Snapshot

Company
Databricks
Category
Operations
Remote
Fully remote
Eligibility
Washington, California
Posted
25 days ago
Salary
Not disclosed

Eligibility

Hiring in: Washington, California

Not available in: NY, CO

About this role

RDQ427R275

Location: San Francisco or Seattle

At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

More about the team:

The Serverless Workspaces team is the engine behind Databricks' shift from a "configure-first" to a "use-now" platform. We are redefining the customer onboarding experience by removing the heavy lifting of cloud infrastructure without complicated networking, storage, and cluster configuration, just instant access to data and AI.

Our mission is to deliver "Workspaces in Seconds." We are building the invisible infrastructure that allows any use (not just infrastructure or IT teams) to spin up a fully governed, secure, and compliant Databricks environment instantly. You will own the strategy for this next-generation platform layer, balancing the simplicity of a SaaS experience with the control enterprise customers demand.

The impact you will have:

• Drive the transition to Serverless: You will lead the strategy to unify the journey to onboard to serverless and classic workspaces and drive 10X usage of serverless in the next year

• Democratize Workspace Creation: You will design and ship flows that allow users to spin up workspaces instantly with little friction while maintaining strict governance guardrails and company policies

• Redefine the "Getting Started" experience: You will lower the barrier to entry by removing the requirement for customers to manage detailed cloud infrastructure configurations before using Databricks but allowing them dial those in when they’re ready

• Solve "Workspace Proliferation": As creating workspaces becomes easier, you will help define the tools and policies that allow Admins to confidently govern increased amounts of workspaces across the enterprise

• Unify the Data Estate: You will work closely with the Unity Catalog and Identity teams to ensure that these new serverless environments seamlessly integrate with a customer’s existing data and security models.

What we look for:

• 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 how to abstract that complexity for end-users.

• Passion for simplification: You have a track record of taking complex technical workflows (like configuring a VPC or peering) and turning them into "one-click" consumer-grade experiences.

• Data-driven mindset: You are comfortable defining and tracking KPIs, such as "Time to First Workspace" or "Serverless Adoption Rate," to measure success.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Zone 2 Pay Range

$172,600—$237,325 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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