Sr. Manager, Compensation Analytics & IntelligenceActive$218K

Databricks
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The opportunity

Databricks is seeking a data-driven compensation professional to lead our Compensation Analytics & Intelligence function. This role will provide centralized compensation analytics and intelligence to drive better, faster, and more consistent decision-making through the effective use of data.

What you'll do

  • Company-wide program analytics (35%): Own enterprise-wide compensation analytics: the market benchmarking process, total comp budget forecasting, and the analytical backbone for major program decisions.

  • AI & data strategy lead (25%): Serve as the Compensation function’s lead on AI and data strategy.

  • Partnership with Finance (20%): Partner with Finance teams on cash compensation 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

  • 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.

What they're looking for

  • Know your tools: Advanced capabilities required in gSheets and Excel. Strong working fluency in SQL and experience with BI / analytics platforms (e.g., Tableau, AI/BI) strongly preferred; Python and hands-on experience applying AI to comp analytics are a meaningful plus.
  • Lead on AI — Genuine enthusiasm and sound judgment for how AI can responsibly: transform compensation work, paired with a sharp instinct for data privacy, governance, and the downstream implications of how sensitive data is handled.
  • Know your craft: Solid foundation in job architecture, comp frameworks, market pricing, year-end and midyear pay cycles, global compensation practices, and pay-for-performance design.
  • Be rational: Ability to balance deep comp knowledge with business solutioning from a first-principles viewpoint.