CSQ427R405

Role overview

We are looking for a Lead Learning Product Specialist to own the platform learning experience for Databricks customers, partners, and internal practitioners. You will sit at the intersection of product, UX, and learning science, building the systems that help data and AI teams build skills needed to become successful and confident users of the Databricks platform.

You’ll define how users discover, practice, and demonstrate skills across in-product journeys, training, and AI-assisted guidance. You will work closely with engineering, design, curriculum, and go‑to‑market teams to translate pedagogical goals into scalable platform capabilities, from adaptive learning flows and assessments to analytics that prove real skill development.

Key responsibilities

• Define and drive the product vision, strategy, and roadmap for AI‑first learning systems on the Databricks platform, anchored on contextual, in the flow of work enablement and a unified skills infrastructure.

• Design experiences that surface targeted knowledge precisely when users need it, triggered by real work context (e.g., usage patterns, errors, task types), reducing interruptions and friction.

• Translate learning and pedagogical goals into platform capabilities such as learner models, skills graphs, progress tracking, adaptive learning paths, assessments, and feedback loops.

• Partner with UX and content design to create intuitive, embedded guidance and learning patterns that feel like part of the workflow, not separate training destinations.

• Collaborate with platform and infrastructure teams to ensure learning and skills systems are reliable, secure, performant, and able to serve global enterprise customers at scale.

• Define and evolve predictive signals and analytics that give proactive visibility into emerging skills and capability gaps, enabling action before they impact business outcomes.

• Build features and tooling that allow enablement teams to deliver at-scale personalization - leveraging AI and automation.

• Provide employees and leaders with transparent views into skills, enablement activities, and progress toward role and organizational goals through dashboards, reports, and in‑product insights.

• Work closely with education, documentation, and curriculum teams to empower them with self‑service configuration and experimentation tools for new learning experiences.

• Engage directly with customers, partners, and internal field teams to deeply understand learning needs across roles and transform these into clear product requirements.

What success looks like in the first 12 months

• A cohesive, AI‑first skills platform and experience is live, guiding users from first login with contextual, just‑in‑time experiences triggered by work context.

• Clear, trusted metrics exist for learning efficacy and skill attainment and used to drive roadmap decisions.

• Predictive insights into emerging capability and skills gaps are available to leaders, enabling proactive interventions before they impact business performance.

• Enablement teams use platform tools you defined to deliver personalized learning and guidance at scale without needing to grow headcount proportionally.

• Learning and skills capabilities are integrated with broader Databricks platform features and measurably improve adoption and expansion.

Qualifications

• 5–8+ years of experience in product management, UX-focused product roles, or learning/education platforms, ideally within B2B SaaS, developer tools, or data/AI products.

• Demonstrated experience owning a product area end to end: defining strategy and roadmap, writing PRDs, collaborating with engineering and design, and shipping impactful user-facing features.

• Experience building or working on learning systems, training platforms, or content/knowledge experiences (LMS, certification, education analytics, in-product guidance, or similar).

• Strong UX instincts and a track record of collaborating closely with designers and researchers to create intuitive flows, information architectures, and content experiences.

• Comfort working with data: defining metrics, instrumenting experiments, and using analytics to understand user behavior, learning outcomes, and skills gaps.

• Excellent written and verbal communication skills, with an ability to explain complex concepts simply and advocate for learners across the organization.

• Experience with AI-powered learning, adaptive systems, or building products that incorporate LLMs into user workflows

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 base 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 anticipated 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
$171,400—$235,750 USD

Zone 2 Pay Range
$154,300—$212,200 USD

Zone 3 Pay Range
$145,800—$200,400 USD

Zone 4 Pay Range
$137,100—$188,550 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

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.

CSQ427R405

Role overview

We are looking for a Lead Learning Product Specialist to own the platform learning experience for Databricks customers, partners, and internal practitioners. You will sit at the intersection of product, UX, and learning science, building the systems that help data and AI teams build skills needed to become successful and confident users of the Databricks platform.

You’ll define how users discover, practice, and demonstrate skills across in-product journeys, training, and AI-assisted guidance. You will work closely with engineering, design, curriculum, and go‑to‑market teams to translate pedagogical goals into scalable platform capabilities, from adaptive learning flows and assessments to analytics that prove real skill development.

Key responsibilities

• Define and drive the product vision, strategy, and roadmap for AI‑first learning systems on the Databricks platform, anchored on contextual, in the flow of work enablement and a unified skills infrastructure.

• Design experiences that surface targeted knowledge precisely when users need it, triggered by real work context (e.g., usage patterns, errors, task types), reducing interruptions and friction.

• Translate learning and pedagogical goals into platform capabilities such as learner models, skills graphs, progress tracking, adaptive learning paths, assessments, and feedback loops.

• Partner with UX and content design to create intuitive, embedded guidance and learning patterns that feel like part of the workflow, not separate training destinations.

• Collaborate with platform and infrastructure teams to ensure learning and skills systems are reliable, secure, performant, and able to serve global enterprise customers at scale.

• Define and evolve predictive signals and analytics that give proactive visibility into emerging skills and capability gaps, enabling action before they impact business outcomes.

• Build features and tooling that allow enablement teams to deliver at-scale personalization - leveraging AI and automation.

• Provide employees and leaders with transparent views into skills, enablement activities, and progress toward role and organizational goals through dashboards, reports, and in‑product insights.

• Work closely with education, documentation, and curriculum teams to empower them with self‑service configuration and experimentation tools for new learning experiences.

• Engage directly with customers, partners, and internal field teams to deeply understand learning needs across roles and transform these into clear product requirements.

What success looks like in the first 12 months

• A cohesive, AI‑first skills platform and experience is live, guiding users from first login with contextual, just‑in‑time experiences triggered by work context.

• Clear, trusted metrics exist for learning efficacy and skill attainment and used to drive roadmap decisions.

• Predictive insights into emerging capability and skills gaps are available to leaders, enabling proactive interventions before they impact business performance.

• Enablement teams use platform tools you defined to deliver personalized learning and guidance at scale without needing to grow headcount proportionally.

• Learning and skills capabilities are integrated with broader Databricks platform features and measurably improve adoption and expansion.

Qualifications

• 5–8+ years of experience in product management, UX-focused product roles, or learning/education platforms, ideally within B2B SaaS, developer tools, or data/AI products.

• Demonstrated experience owning a product area end to end: defining strategy and roadmap, writing PRDs, collaborating with engineering and design, and shipping impactful user-facing features.

• Experience building or working on learning systems, training platforms, or content/knowledge experiences (LMS, certification, education analytics, in-product guidance, or similar).

• Strong UX instincts and a track record of collaborating closely with designers and researchers to create intuitive flows, information architectures, and content experiences.

• Comfort working with data: defining metrics, instrumenting experiments, and using analytics to understand user behavior, learning outcomes, and skills gaps.

• Excellent written and verbal communication skills, with an ability to explain complex concepts simply and advocate for learners across the organization.

• Experience with AI-powered learning, adaptive systems, or building products that incorporate LLMs into user workflows

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 base 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 anticipated 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
$171,400—$235,750 USD

Zone 2 Pay Range
$154,300—$212,200 USD

Zone 3 Pay Range
$145,800—$200,400 USD

Zone 4 Pay Range
$137,100—$188,550 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

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.