Sr. Manager, Compensation Analytics & Intelligence

(GAQ327R301) Databricks is seeking a data-driven

Compensation

professional to lead our

Analytics Intelligence function.

analytics and intelligence to drive better, faster, and more consistent decision-making through the effective use of data.

function at Databricks.

, data, and strategy.

data into insights and operational tooling, serve as the function’s go-to lead for AI and data strategy, and act as a trusted thought partner to senior leaders on the company’s most complex pay challenges — all while maintaining the highest standards for data governance, privacy, and security. In a talent market this dynamic, you will be the person who sees where the market is moving before it moves.

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 who brings rigor, intelligence, and world-class craft to that mission.

analytics: the market benchmarking process, total comp budget forecasting, and the analytical backbone for major program decisions.

function’s lead on AI and data strategy.

budgets and spend. Collaborate on equity budget and spend modeling in close partnership with the Exec Equity comp lead. Competitive intelligence QBR reporting (10%) — Track market trends and spikes/cool-downs across cash, equity, and total rewards.

Strategy program design partnership (10%) — Provide thought partnership on major comp program design and company-wide strategic problems What we look for: We’re looking for someone who has the following strengths Analytics Data fluency — This is the heart of the role. Exceptional analytical skills with a proven ability to transform raw, complex data into insights, tooling, and recommendations. You see the story in the numbers and build the systems that surface it.

Know your tools — Advanced capabilities required in gSheets and Excel. , Tableau, AI/BI) strongly preferred; Python and hands-on experience applying AI to comp analytics are a meaningful plus.

work, paired with a sharp instinct for data privacy, governance, and the downstream implications of how sensitive data is handled.

practices, and pay-for-performance design. Be rational — Ability to balance deep comp knowledge with business solutioning from a first-principles viewpoint. Operational partnership excellence Build innovatively scale effectively — Create frameworks and solutions that not only solve today’s issues but anticipate future needs.

analytics and tooling.

decisions with sound judgment and data-backed recommendations.

practices.