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Sr. Manager, Engineering Performance

Databricks
Full TimeseniorRemote
Remote - Arizona; Remote - California; Remote - Canada; Remote - Colorado; Remote - Illinois; Remote - Massachusetts; Remote - Michigan; Remote - New York; Remote - Texas; Remote - WashingtonRemotePosted February 1, 2026

Job Description

RDQ127R133

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 Performance Engineering team works closely with multiple teams across the company to evaluate the performance of products and features, identify performance bottlenecks, and partner with engineers to solve performance and scalability issues. This implies, among other things, setting performance targets for various software releases, guiding teams to develop performance benchmarks, running competitive benchmark analysis for different Databricks products, doing deep dive analysis to identify performance issues and fix them. As the Sr. Engineering Manager, you will build partnerships with various engineering organizations, drive performance and scalability projects across these teams to deliver the fastest and most cost effective solutions in the market.

Key Responsibilities

  • Technical Leadership: You will lead and guide the team to Identify performance limitations of the entire stack based on telemetry, customer signals, PoCs, and competitive benchmarks, that will result in the best performing system across the industry, when resolved.  
  • Team Development: You will oversee sustained recruitment of top-tier talent, fostering a well-organized and synergistic team structure, and collaborating effectively with internal and external stakeholders
  • Cross-Functional Collaboration: Work closely with product and infrastructure teams to align strategy, execution, and roadmap in alignment with organizational goals and priorities.

What We Look For

  • 5+ years experience in the performance analysis discipline. Ability to identify performance issues, root cause problems, and be able to come up with potential solutions. 
  • Ability to build strong working relationships with developers and field engineers to facilitate triaging and mitigation of performance problems.
  • At least  3 years of experience in managing top-tier engineering teams
  • BS in Computer Science (Masters or higher level of education preferred)
  • Expertise in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards. Experience up-leveling teams via hiring top-notch talent and growing existing team members.

 

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

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta

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