Databricks

Databricks

Director, Compensation

United States · Director

Sponsorship not specified$218k-$300kDetected 1 day ago
PythonSQLDatabricksSparkData VisualizationExcelM&ACompensationLeadershipCollaborationMentoring

About the role

  • The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.
  • Based on the factors above, Databricks anticipated utilizing the full width of the range.
  • For more information regarding which range your location is in visit our page here.

Responsibilities

  • Leading, coaching, and developing a team of three to four client compensation partners (25%)
  • Partnering with the VP Rewards and other team members to drive enterprise-wide compensation strategy, design, and program delivery (30%)
  • Collaboration with People team members, business leaders, and other cross-functional partners on complex, sensitive compensation matters (25%)
  • Drive accountability - Set clear goals and expectations, create feedback loops, and hold the team to a high bar while remaining a supportive and empowering manager
  • Build innovatively & scale effectively - Architect frameworks and solutions that address today's challenges while anticipating the needs of a rapidly scaling organization; champion consistency and repeatability without sacrificing flexibility

Compensation

  • Know your craft - Deep mastery of job architecture, compensation frameworks, market pricing, year-end and midyear pay cycles, global compensation practices, and pay-for-performance design; demonstrated experience designing and scaling programs across a fast-growing, global organization
  • Know the competition - Expert-level knowledge of tech compensation practices, particularly around equity strategy (new hire, refresh, and performance-based), and an ability to benchmark and evolve programs to stay ahead of the market
  • Be rational - Ability to hold the tension between compensation philosophy, first-principles reasoning, and pragmatic business solutioning; comfortable making and defending difficult tradeoffs in ambiguous situations
  • Develop talent - Proven track record of leading, mentoring, and growing a team of compensation professionals; ability to set a clear vision, delegate with confidence, and create an environment where the team does their best work
  • Model the craft - Remain hands-on where needed; serve as a thought partner and technical escalation point for your team on complex or high-stakes compensation decisions
  • Leverage AI and automation - Define and execute a roadmap for next-generation compensation tooling and data infrastructure; actively leverage AI to improve market pricing, decision quality, manager enablement, and workflow efficiency; champion a culture of continuous improvement through technology

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.

Company info

  • Databricks is seeking a seasoned compensation leader to serve as a Director, Compensation, driving strategic impact across the business while leading and developing a team of client compensation partners.
  • Reporting to the VP, Total Rewards, this role is responsible for building and delivering best-in-class compensation programs that help attract, retain, and motivate world-class talent across Databricks.
  • 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 leader who combines deep technical compensation expertise with exceptional people leadership and a passion for building scalable, equitable programs.
  • At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.

Equal opportunity

  • Our Commitment to Diversity and Inclusion

This listing is sourced directly from Databricks's careers page and normalized into a canonical job model.