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Databricks

Builds cloud software for data analysis and AI

Product Finance Director - R&D Capital Allocation & Engineering Operations

Corporate Finance & FP&AConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 10 years of experience in Strategic/Product Finance or R&D financial planning and analysis.
  • Deep experience managing large-scale R&D operating expenses, headcount capacity modeling, and multi-site workforce planning within a high-growth enterprise software or cloud company.
  • A proven track record of partnering directly with senior Engineering, Product Operations, and People/Workplace executives to drive capital allocation and operational rigor.
  • Systems-level thinking and demonstrated ability to re-engineer financial processes from scratch, spanning headcount tracking, procurement, close, and Sarbanes-Oxley controls, to support rapid scale.
  • Experience building, leading, and developing high-output finance teams in fast-moving environments.

Responsibilities

  • Establish frameworks to measure product-level return on investment across a fast-moving platform with high engineering velocity.
  • Operationalize return-on-investment metrics so they directly inform product investment and resource allocation decisions.
  • Partner with Engineering to model how AI developer tooling and internal token spend scale alongside headcount, quantifying the tradeoff between human capital and compute capital.
  • Measure the end-to-end cost of AI-enabled engineering, including second-order impacts on cloud spend, and partner with Engineering to optimize investments.
  • Drive multi-year headcount planning across global engineering hubs, balancing cost per hire, talent density, and university recruiting pipelines.
  • Partner with Workplace and Facilities leadership to synchronize R&D hiring roadmaps with global real estate strategy and multi-year capital expenditure planning.
  • Build scalable, automated R&D finance workflows across headcount management, purchase order planning, monthly accruals, and Sarbanes-Oxley audit compliance.
  • Use the Databricks platform to modernize internal finance tooling and deliver self-service operational visibility to engineering leaders.
  • Build, mentor, and scale a high-performing team of finance professionals able to operate across strategic capital allocation and operational execution.

Desired Qualifications

  • Direct experience analyzing cloud development/test infrastructure and AI tooling or token costs.
  • Experience attributing shared engineering and platform R&D costs across a complex, multi-product portfolio to establish product-level profitability.
  • Hands-on proficiency with SQL, Python, or notebook environments, especially Databricks, to automate reporting and provide self-service insights from large operational datasets.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$32.1B
Headquarters
San Francisco, CA
Founded
2013

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