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Databricks

Senior Engineering Manager for Workspace Platform

Databricks is hiring a Senior Engineering Manager for Workspace Platform in San Francisco, United States. It pays $217k-$312k a year and Level rates it ; you can apply on Databricks.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • Level classifies it as a senior role.
  • Level lists 904 other open roles at Databricks.

AI in this role

RDQ225R488

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

The Workspace Platform team is on an ambitious mission to scale our customer base 100x and support the future of agentic AI workloads. Our goal is to build a unified, consistent, and foundational Shared Platform for the entire Databricks Workspace experience.

As a Senior Engineering Manager on the Workspace Platform team, you will lead the development of unified infrastructure powering critical customer-facing capabilities across multiple Databricks products, including Content Discovery (akin to Google Search), Content Organization (akin to Google Drive), Collaborative code editing, and Repository management (akin to Github). This is a high-impact, exciting opportunity to guide a team of ~20 software engineers in creating platform features, intuitive workspace experiences, and partner integrations that are essential to Databricks' expansion and user adoption.

The impact you will have:

  • Strategy & Vision: Define and drive the technical strategy for the Workspace Platform, including building over 16 shared capabilities that underpin the entire Databricks experience.
  • Execution Ownership: Own the roadmap, execution, and delivery for the platform, ensuring all team deliverables meet the highest standards of quality and timeliness.
  • Engineering Excellence: Establish and enforce team best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations for high-volume distributed systems.
  • Cross-Functional Collaboration: Partner closely with teams across the organization, including those developing vertical product experiences (Lakehouse Platform, SQL Warehouse, AI/BI Dashboards, UC Platform) and core infrastructure, to ensure seamless integration and innovation.

What we look for:

  • Experience: 15+ years of software engineering experience with a strong track record of technical leadership and impact.
  • Management: 5+ years of engineering management experience, including experience managing other managers.
  • Scaling: Proven experience scaling engineering teams from 10 to 30+ engineers.
  • Platform Expertise: Experience leading platform teams and backend developers in a SaaS environment.
  • Technical Depth:
    • Experience designing and building scalable distributed systems.
    • Familiarity with building services on top of containerization technologies.
    • Expertise in distributed systems, major cloud platforms (AWS, Azure, GCP), and modern web application architectures.
  • Collaboration: Strong ability to collaborate across product, engineering, and business teams to align technical strategy with core company growth objectives.
  • Passion: A passion for building and scaling robust, high-performance platforms.

 

 

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$217,000—$312,200 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At 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.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

How we rate this

Senior Engineering Manager for Workspace Platform at Databricks rates 23 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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