Skills Systems Architect
Databricks · United States
About this role
**Skills Systems Architect — Databricks** ## About the Role Databricks is building a way to define, measure, and develop technical capability across learner audiences (employees, customers, and partners). In this builder role, you’ll own the systems that connect roles, skills, content, and credentials—along with the instrumentation that shows where capability actually stands. ## What You’ll Own ### Skills taxonomies, capability models, and learning context - Define skills taxonomies that make up technical capability and how they’re organized (what skills exist, adjacency, prerequisites, how quickly they go stale, and learner sources). ### Observability and measurement - Stand up instrumentation and AI-informed signals to show where capability stands and where it’s drifting. - Develop live signals (not quarterly/monthly health indices) to track how skills move and evolve. - Anticipate where capability demand is heading by tracking product releases, market shifts, and role evolution. ### AI-native tooling - Build software that maintains the skills taxonomy and capability model, including LLM-driven skill extraction/organization, agentic pipelines to keep them current, automated drift/gap detection, and APIs. - Make the model reusable across the enterprise (not just a training-only asset). ## Impact You’ll Have You’ll work upstream across multiple teams and functions: - **Anywhere skills show up in products:** Define what technical capability means and what evidence counts. - **Content and curriculum:** Influence what gets built next and why; learning context is a key input to generative content. - **Learning architecture & in-product training:** Inform where learning belongs and how it’s presented; pathways are assembled using the model/taxonomy. - **Certification & accreditation:** Ground skills assessment to guide and accelerate exam developers. - **Learning & enablement:** Provide a current view of capability across every audience with a shared model for planning. ## What We’re Looking For - Experience in technical training, learning, enablement, or product education (data & AI, cloud, or similar product categories). - Experience designing capability/skills models and the systems around them (modeling, measurement, instrumentation). - Builder mindset: use **Python** and **SQL**, build apps with AI assistance, and wire up pipelines/tooling. - AI-native approach: use AI for extraction/assessment, agentic workflows, and evaluation—knowing when to use AI and when not to. - Track record of moving strategy as an IC through analysis and clear writing. ### Nice to Have - Familiarity with off-the-shelf skills-intelligence tooling and build-vs-buy tradeoffs. - Experience instrumenting capability data across multiple audiences. ## What Success Looks Like in Year One - A live skills taxonomy, capability model, and learning context resources are published and used by content, learning, and certification teams. - Build/refresh/retire decisions leverage the taxonomy/model so content keeps pace with the product and investment targets real demand and skill gaps. - In-product training uses the model to target and measure learning, giving learners visibility into progress and stakeholders insight into attainment. - Teams that bring skills into products use the same model so skills mean the same thing everywhere. ## Pay Range Transparency (USD) - **Zone 1:** $117,400 — $161,350 - **Zone 2:** $105,600 — $145,200 - **Zone 3:** $99,800 — $137,150 -
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.