Senior Engineering Manager for Self-Serve (Learning)
Databricks · Mountain View, California · Engineering · listed August 21, 2026
The shape of it
Seniority
Manager
Experience asked
2–15 years
Where
Not stated
Stated pay
$222,000 – $300,000 USD
Requirements listed
10
Length
911 words
In the posting’s own words
As a Senior Engineering Manager on the Self-Serve team, you will lead the Learning bet end to end across two sides: self-paced learning — a place to learn any Databricks skill, hands-on labs that spin up inside a real workspace, and a durable skill profile a learner carries across jobs — and enterprise-managed learning, giving admins the tools to assign, track, and grow learning inside their orgs. AI is central to both: a content-generation agent that scales the catalog far past what we could author by hand, and an AI tutor that guides learners hands-on inside the product. This is a genuine 0→1 product with real systems depth — on-demand provisioning, identity, sandboxing, and an interactive learning engine that must scale to millions of learners — and you'll grow and lead a team of ~12 engineers (planned to roughly double) to build it.
What it asks for · 10
- Experience:
- 15+ years of software engineering experience with a strong track record of technical leadership and impact.
- 5+ years of engineering management experience, including 2+ years managing other managers (or clear readiness to).
- Technical Depth: A Staff engineer caliber IC background before pivoting to management, with full-stack experience (including back-end, not purely front-end/UI); comfort leading a mix of front-end and full-stack engineers.
- Scaling: Proven experience scaling engineering teams from 10 to 30+ engineers.
- Product & Domain Fit:
- A track record building and scaling consumer-facing products, ideally taking early-stage products from 0→1 through scale. Scope- and impact-driven over team-size-driven.
- Genuine excitement for product-led growth and putting AI to work in a real product.
- Systems at scale: Experience designing scalable, distributed, customer-facing systems, ideally in a SaaS environment.
- Collaboration: Strong ability to align technical strategy with company growth objectives across product, engineering, and go-to-market partners.
What the job covers
- Strategy & Vision: Define and drive the technical and product strategy for Learning, and tie it into the broader self-serve growth motion.
- Execution Ownership: Own the roadmap, execution, and delivery — taking a 0→1 product from early signal to millions of learners at the highest standards of quality.
- Engineering Excellence: Establish team best practices — design reviews, code quality, testing, and performance for high-scale, interactive systems.
- Cross-Functional Collaboration: Partner closely across R&D, the Learning & Enablement org, Marketing (university and online channels), and Field Engineering to align the product with how learners actually reach and adopt Databricks.
Tools and skills named
Data
- Databricks7×
Go to market
- Go-to-market
- SaaS
Product & design
- Product strategy
- Roadmap
Ways of working
- Cross-functional
- Testing
Words the posting leans on
- product10×
- learning8×
- engineering7×
- experience7×
- learners6×
- data5×
- engineers4×
- growth4×
- scale4×
- systems4×
- technical4×
- building3×
- inside3×
- learn3×
- real3×
- scaling3×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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