Sr. Compensation Manager
DatabricksMountain View, California; San Francisco, CaliforniaPosted 24 February 2026
Job Description
GAQ127R143
While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered.
Databricks is seeking a strategic and experienced compensation lead to serve as a trusted partner to founders and senior leadership in our RD org (technology and product teams). This is a key role on the Compensation function at Databricks, reporting to the Senior Director of Compensation. This role will support long-term business objectives by working within the overall Compensation philosophy to co-create compensation models that help attract, retain and motivate world-class technical talent.
At Databricks, we don't believe compensation is just a number; it's a tool to recognize that every employee is an owner and a part of our success. We are looking for a team member with a solid foundation and history of success in doing just that!
Scope of the role
This is a hands-on, high-impact role that will effectively cover below areas and the anticipated time spent on each:
Compensation solutioning for RD Talent (40%)
Managing Compensation processes through the employee life cycle (30%)
Contributing to building and delivering enterprise-wide compensation programs/ frameworks (30%)
Requirements
We’re looking for someone who has the following muscles:
Comp expertise
Know your craft - Job architecture, Comp frameworks, Market pricing, Year-end and Midyear pay cycle, global compensation practices, pay for performance design
Know your data - Exceptional analytical skills with the ability to synthesize complex data into clear outputs and recommendations. Analyze competitive trends in cash, equity, and total rewards to inform decision-making and tradeoffs. Advanced capabilities required in gSheets, excel. We’ll love it if you know tableau, SQL, python or have used AI for comp analytics though not a requirement
Know the competition - Deep expertise in tech compensation practices, especially around new-hire and refresh equity strategies in the tech sector
Be rational - Ability to balance comp knowledge with business solutioning from a first principles viewpoint.
Operational and partnership excellence
Build innovatively scale effectively - create innovative frameworks/solutions to not just solve today’s issues but also thinking ahead and anticipating future needs
Operational capability - Ability to connect the dots between systems, players, programs to seamlessly deliver compensation programs/ products
Savvy collaborator - Partner closely with founders and executive leadership to pre-empt, understand and solve business needs. Navigate at times competing priorities and opinions to drive the best outcomes
Trusted advisor - Act as a trusted advisor on compensation decisions, including offers, promotions, leveling, retention and MA scenarios. Support sensitive, high-stakes compensation decisions with sound judgment and data-backed recommendations.
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 .
Zone 1 Pay Range
$217,800
$299,550 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 Intellig ... (truncated, view full listing at source)
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