# Skills Systems Architect at Databricks

> Build systems that define, measure, and track technical skills and capability across Databricks' employee, customer, and partner audiences.

- Company: Databricks (databricks.com)
- Location: United States
- Places: United States
- Posted: 2026-10-07
- Work mode: Remote
- Apply: https://databricks.com/company/careers/open-positions/job?gh_jid=8824173002
- Page: https://ye.saranatour.dev/jobs/skills-systems-architect-databricks-kn72f68x3xspv8z9xasc5nf2hd8hcphe

## The posting

Skills Systems Architect
Databricks · United States

FEQ227R209

## About the Role

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.

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.

## What You'll Own

### Skills taxonomies, capability models, and learning context

- 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.

### Observability and measurement

- 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.

### AI-native tooling

- 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.

## Impact You'll Have

You will sit upstream of and across several teams and functions:

- **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.
- **Content and curriculum.**The skills taxonomy and capability model influence what gets built next and why. Learning context is a critical input to generative content.
- **Learning architecture and in-product training:**Your work informs what learning belongs where and how it’s presented. Pathways are assembled with the model and taxonomy instead of mapped by hand; in-product training surfaces them to learners.
- **Certification & accreditation**. The capability model grounds skills assessment to guide and accelerate exam developers.
- **Learning & enablement**. You give the organization a current view of capability across every audience, and a shared model to build and plan against.

## What We'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 stan