Databricks

Senior Engineering Manager for Self-Serve (Learning)

Databricks$222K — $300K *
Education, Government & Non-Profit
11 - 15 years of experience
Job Overview by Ladders

Qualifications

  • 15+ years of software engineering experience with proven technical leadership.
  • 5+ years in engineering management, including managing other managers.
  • Staff engineer caliber experience with full-stack technical expertise.
  • History of scaling engineering teams from 10 to over 30 engineers.
  • Experience in building and scaling consumer-facing, product-led growth initiatives.
  • Familiarity with designing scalable, distributed customer-facing systems, preferably in a SaaS context.
  • Strong alignment capability between technical strategy and broader company growth goals.

Responsibilities

  • Define and drive the product strategy for Learning in alignment with self-serve growth.
  • Own the product roadmap and execution, ensuring high standards from early stages to mass adoption.
  • Establish engineering best practices focused on code quality and system performance.
  • Collaborate cross-functionally with R&D, Learning & Enablement, Marketing, and Field Engineering to align product development with learner engagement.

Benefits

  • Comprehensive benefits and perks to meet diverse employee needs.
  • Eligibility for annual performance bonuses and equity options.
  • Support for personal skill development and professional growth opportunities.
Full Job Description
RDQ426R220

The Self-Serve team owns Databricks' product-led growth motion - the experience that takes someone from "I just heard about Databricks" to succeeding on the platform entirely on their own. Our most ambitious bet is Learning: making Databricks the place where anyone interested in data + AI comes to learn, and building the largest community of active, capable learners in the world. It's a long game with a simple thesis - if people learn data + AI on Databricks, it becomes ubiquitous with the field itself, driving adoption and revenue.

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 01 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.

The impact you will have:
  • 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 01 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.


What we look for:
  • 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 01 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.


Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$222,000-$300,000 USD

BenefitsAt Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

About Databricks

Databricks is a unified analytics platform that provides data engineering, collaborative data science, and machine learning capabilities. The company was founded in 2013 by the original creators of Apache Spark, a popular open-source big data processing engine. Databricks provides a cloud-based platform that allows data teams to collaborate and build data pipelines, run machine learning models, and perform advanced analytics. The company has raised over $1 billion in funding and is valued at $38 billion as of November 2021.
Learn more about Databricks
Size
2,000 employees
Industry
Founded
2013

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