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Benefits Diversity Engineering Research Students & new grads Back to search results Sr Product Manager, Employee Experience Mountain View, California; San Francisco, California Apply now Sr Product Manager, Employee Experience Location: San Francisco, CA or Mountain View, CA GAQ426R322 About Databricks At Databricks, our mission is to help data teams solve the world’s toughest problems and that starts with empowering our own employees. The Databricks IT organization is a product-led team that builds intelligent, scalable systems to make every Brickster’s workday simpler, faster, and more connected. We’re reimagining how employees and managers interact with internal tools; designing a unified, AI-driven experience that integrates data, insights, and workflows across the company. We’re looking for a Senior Product Manager (L5) to lead strategy and delivery for our newly formed People Pod. This role is a "zero to one" initiative focused on building next-generation agentic workflows on top of Databricks to fundamentally enhance internal employee experience tools and extend capabilities far beyond traditional systems like Workday. The Opportunity Managers and employees at Databricks interact with dozens of systems every week, from Workday to performance and onboarding tools, often switching contexts and duplicating effort. This team is responsible for defining and delivering product vision to simplify and unify the employee experience, designing an integrated, intelligent automation layer that sits on top of our systems of record to surface the right tasks, insights, and actions in one place. As the Product Manager for the People Pod, you will own a highly visible, zero-to-one product area, driving product thought leadership to shape how Databricks scales its internal workforce lifecycle through advanced automation and specialist domain applications. What You’ll Do Own the Zero-to-One Vision: Define and evolve the long-term strategy for the unified employee and manager experience, specifically focusing on advanced agentic workflows and automation tailored to the People function. Drive Product Strategy & Automation: Partner closely with developers, engineering teams, and stakeholders across People Operations and IT to design, build, and deploy intelligent agentic automation workflows on the Databricks platform. Domain Leadership: Serve as the primary product leader specializing in talent acquisition, hiring processes, and performance management workflows, transforming standard internal tools into highly optimized, automated experiences. Execute and Measure: Define success metrics (adoption, efficiency, engagement, automation accuracy) and use data-driven insights to guide rapid iteration and development within an evolving field. Influence and Collaborate: Report directly to VP of Product in IT and work cross-functionally to align engineering, design, and senior leadership around the automated product vision, evangelizing the roadmap in company-wide productivity and AI discussions. What You Bring 5+ years of product management experience , with a proven track record leading specialized, highly technical, or zero-to-one enterprise and internal product initiatives. Specialist Domain Expertise: Deep background in human resources and people-process functions, specifically with concrete experience in hiring, talent acquisition, employee experience and performance management . Agentic Automation & Advanced AI: Hands-on experience or a strong technical understanding of agentic automation , LLM orchestration, and modern AI-driven workflows to streamline operational bottlenecks. Strategic & Product Thought Leadership: Demonstrated ability to own a product domain end-to-end, linking automation outcomes directly to corporate scaling and employee experience goals. Technical & Data Fluency: Strong understanding of building on advanced data platforms, user-centered design, data-informed development, and modern enterprise governance practices (e.g., RBAC/ABAC). Ambiguity Champion: Highly comfortable leading through extreme ambiguity, managing complex stakeholder landscapes, and collaborating directly with engineering pods to build applications from scratch. Preferred
Qualifications Experience developing custom productivity applications or automation layers on data platforms (such as Databricks). Familiarity with enterprise HR ecosystems like Workday, ServiceNow, or similar core systems of record, specifically regarding their API limitations and integration surfaces. Why You’ll Love This Role This is an opportunity to build one of Databricks’ most visible and innovative internal products, touching every employee and manager. You’ll define how the company experiences its own culture, systems, and data, while shaping a product that directly leverages Databricks’ own bleeding-edge technology. You’ll have the autonomy to create the future of how Databricks works, operating in a highly strategic environment with a direct line to leadership. 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 1 Pay Range $145,000 — $199,300 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. Why Databricks Discover For App Developers For Executives For Startups Lakehouse Architecture Databricks AI Research Customers Customer Stories Partners Partner Overview Partner Program Find a Partner Partner Spotlight Cloud Providers Partner Solutions Why Databricks Discover For App Developers For Executives For Startups Lakehouse Architecture Databricks AI Research Customers Customer Stories Partners Partner Overview Partner Program Find a Partner Partner Spotlight Cloud Providers Partner Solutions Product Databricks Platform Platform Overview Application Development Artificial Intelligence Business Intelligence Business Productivity Customer Data Platform Data Engineering Data Warehousing Database Governance Security Sharing Pricing Pricing Overview Pricing Calculator Open Source Integrations and Data Marketplace IDE Integrations Partner Connect Product Databricks Platform Platform Overview Application Development Artificial Intelligence Business Intelligence Business Productivity Customer Data Platform Data Engineering Data Warehousing Database Governance Security Sharing Pricing Pricing Overview Pricing Calculator Open Source Integrations and Data Marketplace IDE Integrations Partner Connect Solutions Databricks For Industries Communications Financial Services Healthcare and Life Sciences Manufacturing Media and Entertainment Public Sector Retail View All Cross Industry Solutions AI Agents AI Governance Cybersecurity Marketing Data Migration Forward Deployed Engineering Solution Accelerators Solutions Databricks For Industries Communications Financial Services Healthcare and Life Sciences Manufacturing Media and Entertainment Public Sector Retail View All Cross Industry Solutions AI Agents AI Governance Cybersecurity Marketing Data Migration Forward Deployed Engineering Solution Accelerators Resources Documentation Customer Support Community Learning Training Certification Free Edition University Alliance Databricks Academy Login Events Data + AI Summit Data + AI World Tour AI Days Event Calendar Blog and Podcasts Databricks Blog AI Blog Data Brew Podcast Champions of Data & AI Podcast Resources Documentation Customer Support Community Learning Training Certification Free Edition University Alliance Databricks Academy Login Events Data + AI Summit Data + AI World Tour AI Days Event Calendar Blog and Podcasts Databricks Blog AI Blog Data Brew Podcast Champions of Data & AI Podcast About Company
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Salary
$145,000 - $199,300
Location
San Francisco, Mountain View
Total raised
$130.0M
Last stage
Series B
Investors
No applications, no recruiter spam. Just the intro.
A few questions to make sure this role is the right shape for you. Two minutes.
I write the intro, send it to the founder, and handle the back-and-forth.
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.