Skills Systems ArchitectActive$139K

Databricks
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The opportunity

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…

What you'll do

  • 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.

  • 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.

  • 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.

  • 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 expose it all.

  • Make the model reusable enterprise context that other systems, teams, and: products build on vs. a training-only asset.

  • Anywhere skills show up in products: You define what technical capability means and what evidence counts, so wherever skills are inferred, captured, or recognized, it reflects real technical work and skills & abilities.

What they're looking for

  • Experience in technical training, learning, enablement, or product education: in data & AI, cloud, or comparable product categories.
  • Experience designing capability or skills models and the systems around them,: spanning modeling, measurement, and instrumentation.
  • A builder mindset. Ability to use Python and SQL and build apps, with AI: assistance, and wire up pipelines and stand up tooling yourself.
  • AI-native. AI tooling is how you build and reason, from extraction and: assessment to agentic workflows and evaluation. You understand when to reach for AI and when not.
  • A track record of moving strategy as an IC through analysis and clear writing.
  • Familiarity with off-the-shelf skills-intelligence tooling and build-vs-buy tradeoffs.
  • Experience instrumenting capability data across several audiences.