Sr. Manager, Compensation Analytics & Intelligence

Reposted 4 Hours Ago
Hiring Remotely in United States
Remote
218K-300K Annually
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
Lead compensation analytics and AI strategy to transform compensation data into insights, tooling, and forecasts. Own market benchmarking, total comp budget forecasting, competitive intelligence, and partner with Finance and senior leaders on compensation design and equity modeling while ensuring data governance and privacy.
Summary Generated by Built In

(GAQ327R301)

Databricks is shaping the future of data and AI, and building world-class engineering teams requires world-class talent strategy. This role serves as the central driver for compensation intelligence and analytics, empowering faster, highly informed, and consistent organizational decision-making through data-driven insights.

Reporting directly to the VP of Total Rewards, this is a strategic builder’s role tailored for an expert operating at the intersection of compensation, advanced analytics, data engineering, and business strategy.

Scope of the Role
  • AI & Data Strategy Lead (60%) — Serve as the lead subject matter expert on AI and data strategy within the Compensation function. Collaborate closely with People Intelligence and IT teams to design, architect, test, and deploy automated workflows and AI-driven solutions across core compensation processes.
  • Enterprise Program Analytics (30%) — Lead company-wide compensation analytics, overseeing total compensation budget forecasting and providing the analytical framework supporting major executive program decisions.
  • Market Intelligence & Executive Reporting (10%) — Monitor, evaluate, and report on market dynamics across cash, equity, and total rewards programs through Quarterly Business Reviews (QBRs) and executive summaries.
What You'll Bring

Analytics

  • Data Fluency & System Architecture — Core competency in transforming complex, unstructured datasets into actionable business insights, predictive tooling, and strategic recommendations. Capability to synthesize numbers into cohesive narratives and build scalable systems designed to anticipate future business needs.
  • Technical & Platform Expertise — Advanced proficiency in Google Sheets and Excel. Strong working knowledge of SQL and hands-on experience with business intelligence platforms (e.g., Databricks) is highly preferred. Proficiency in Python and practical application of AI in compensation analytics are significant advantages.
  • AI Leadership & Data Governance — Demonstrated commitment to leveraging AI to responsibly enhance compensation processes, combined with a strict adherence to data privacy, confidentiality, governance, and compliance protocols.

Compensation

  • Core Compensation Mastery — Deep expertise in job architecture, compensation structures, market benchmarking, merit and equity review cycles, offer structuring, and financial modeling.
  • Business Acumen & Strategic Partnership — Proven ability to translate business requirements into pragmatic compensation strategies. History of partnering effectively with Finance and senior leadership, navigating complex stakeholders, and guiding high-stakes 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 base 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 anticipated 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
Zone 2 Pay Range
$196,100—$269,600 USD
Zone 3 Pay Range
$185,200—$254,650 USD
Zone 4 Pay Range
$174,200—$239,600 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Skills Required

  • Advanced capabilities in Google Sheets and Excel
  • Exceptional analytical skills transforming complex compensation data into insights and operational tooling
  • Experience in compensation: job architecture, comp frameworks, market pricing, pay cycles, global compensation practices, pay-for-performance design
  • Experience owning market benchmarking and total compensation budget forecasting
  • Experience partnering with Finance and senior leadership on compensation budgeting and equity modeling
  • Lead on AI and data strategy with strong attention to data governance, privacy, and security
  • Strong working fluency in SQL
  • Experience with BI/analytics platforms (e.g., Tableau, AI/BI)
  • Python experience and hands-on application of AI to compensation analytics

Databricks Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.

  • Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage alongside mental-health resources, wellness reimbursements, and business travel insurance. Offerings are described as broad and modern, with core health coverage consistently emphasized.
  • Parental & Family Support — Paid parental leave is explicitly called out, with details such as up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents in the U.S. Public materials also reference family-forming support, reinforcing the focus on families.
  • Wellbeing & Lifestyle Benefits — Wellness programs and perks include gym reimbursement, periodic wellness events (e.g., yoga, massages), and in-office meals and snacks in many locations. Personal development funds and discounts further enhance lifestyle and growth support.

Databricks Insights

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The Company
HQ: San Francisco, CA
2,200 Employees
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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