Skills Systems Architect

<p data-pm-slice="1 1 []">FEQ227R209</p> <h2>About the Role</h2> <p>Databricks needs to understand what technical capability looks like across several large, fast-moving populations: employees, customers, and partners. Today that happens through role-based learning pathways and product-aligned enablement, an approach that can't keep pace with how quickly the platform, technology, and roles change. AI has also collapsed the half-life of technical proficiency, and for the first time, it makes a living, self-maintaining model of capability possible.</p> <p>In this builder role, you'll own systems for defining, measuring, and developing technical capability across Databricks learner audiences. You'll build a capability model that ties roles, skills, content, and credentials together and the instrumentation that shows where capability actually stands.</p> <h2>What You'll Own</h2> <h3>Skills taxonomies, capability models, and learning context</h3> <ul> <li>Define the skills taxonomies that make up technical capability and shape how they’re organized; what skills exist, which are adjacent, which are prerequisites, how quickly they go stale, and what sources are available to learners for developing and maintaining them.</li> </ul> <h3>Observability and measurement</h3> <ul> <li>Stand up instrumentation and AI-informed signals that show where capability stands and where it's drifting. Develop live signals, not a quarterly or monthly health index, to show how skills are moving and evolving.</li> <li>Anticipate where capability demand is heading. Product releases, market shifts, and role evolution are constant; track changes closely so emerging skills surface early and content and programs stay ahead of change.</li> </ul> <h3>AI-native tooling</h3> <ul> <li>Build the software that maintains the skills taxonomy and capability model, including LLM-driven skill extraction and organization, agentic pipelines that keep them current, automated drift and gap detection, and APIs that