Lead Learning Product Manager
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will own the learning platform experience, define product strategy and roadmaps, and translate pedagogical goals into scalable capabilities. You will build adaptive learning, assessment, analytics, and personalization features, partner across product disciplines, and turn customer needs into product requirements.
Requirements
- 5–8+ years of experience in product management, UX-focused product roles, or learning and education platforms.
- Experience owning a product area end to end, including strategy, roadmap, PRDs, collaboration, and shipping features.
- Experience with learning systems, training platforms, or content and knowledge experiences.
- Experience collaborating with designers and researchers on user flows, information architecture, and content experiences.
- Experience defining metrics, instrumenting experiments, and using analytics.
- Excellent written and verbal communication skills.
- Experience with AI-powered learning, adaptive systems, or LLM-enabled user workflows.
Responsibilities
- Define and drive the product vision, strategy, and roadmap for AI-first learning systems.
- Design contextual learning experiences and adaptive learning flows.
- Translate learning goals into learner models, skills graphs, assessments, and feedback loops.
- Partner with UX and content design on embedded guidance and learning patterns.
- Collaborate with platform and infrastructure teams on reliable, secure, scalable learning systems.
- Define predictive signals and analytics for skills and capability gaps.
- Build personalization features and tooling using AI and automation.
- Provide skills and enablement insights through dashboards, reports, and in-product experiences.
- Enable education, documentation, and curriculum teams with self-service tools.
- Engage customers, partners, and field teams to define product requirements.