Partner Enablement Technical Lead

Databricks
United StatesPosted 4 March 2026

Job Description

<p data-pm-slice="1 1 []">FEQ227R158</p> <h3><strong>Role Overview</strong></h3> <p>Databricks is a partner-first company. Our exponential growth is fueled by the success of our partner ecosystem. As the <strong>Partner Enablement Technical Lead</strong>, you will be a key architect of our global partner enablement strategy. You will design, build, and execute high-impact learning programs—ranging from technical readiness to advanced certifications—ensuring our partners can deliver Databricks projects with total confidence.</p> <p>This role demands a master of strategic planning and operational excellence. You will manage complex global initiatives, collaborate with cross-functional stakeholders, and translate business needs into world-class learning experiences. You are joining a high-performance team that recently tripled our trained partner base in just 12 months, using innovative learning models to transform the Databricks ecosystem at scale.</p> <h3><strong>Key Responsibilities</strong></h3> <ul> <li><strong>Design Technical Enablement Programs: </strong>Architect comprehensive enablement programs such as Advanced Technical Academies, Delivery Specializations, and technical onboarding to drive partner technical proficiency. In collaboration with Subject Matter Experts, you will define end-to-end learning paths, encompassing curriculum, assessments, and success metrics</li> <li><strong>Strategic Alignment:</strong> Partner with leadership and partner-facing teams to identify critical skills gaps and translate business requirements into high-impact enablement initiatives.</li> <li><strong>Technical Roadmap Leadership:</strong> Own the roadmap for technical programs, including large-scale learning events, global workshop schedules, and GTM strategies for enablement.</li> <li><strong>Performance Accountability:</strong> Drive results for your partner portfolio, maintaining full ownership of key metrics such as training completion and certification targets.</li> <li><strong>Data-Driven Insights:</strong> Monitor and analyze KPIs (Certification rates, ROI, and program impact) to continuously optimize enablement effectiveness.</li> <li><strong>Quality Assurance Coaching:</strong> Oversee the technical integrity of programs launched across the team. Evaluate and coach cross-functional training resources to ensure "best-in-class" delivery.</li> </ul> <h3><strong>Minimum Qualifications</strong></h3> <ul> <li><strong>Education:</strong> Bachelor’s degree in a technical discipline or equivalent practical experience.</li> <li><strong>Experience:</strong> 7+ years of experience developing and scaling technical learning programs within a global enterprise tech ecosystem.</li> <li><strong>Technical Depth:</strong> Deep understanding of Data AI technologies (Data Warehousing, Data Transformation, ML, and Generative AI); ideally holds at least one industry certification in these areas.</li> <li><strong>Consulting Background:</strong> Proven experience as part of a technical delivery team, successfully implementing Data AI projects for external clients.</li> <li><strong>Ecosystem Knowledge:</strong> Strong understanding of the <strong>System Integrator (SI)</strong> business model and how technical partners successfully go to market.</li> <li><strong>Program Management:</strong> Proven track record of managing technical competency models and learning journeys for large, geographically dispersed teams.</li> <li><strong>Communication:</strong> Exceptional verbal and written communication skills with the ability to influence senior cross-functional stakeholders.</li> </ul> <h3><strong>Preferred Qualifications</strong></h3> <ul> <li>Strong background in the <strong>Generative AI</strong> landscape.</li> <li>Experience scaling technical enablement within "Hyperscaler" environments (AWS, Azure, or GCP) or similar high-growth cloud partner ecosystems.</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="description">< ... (truncated, view full listing at source)