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

Databricks • San Francisco, CA

25d

About The Position

Databricks is seeking a Product Finance leader to own R&D capital allocation and engineering operations as the company scales. The role partners with senior Engineering and Product Operations leaders and spans product-level R&D return on investment, global workforce and location strategy, and the economics of AI-enabled software development.

The Director will establish product-level ROI frameworks and ensure those metrics inform investment and resource-allocation decisions. In partnership with Engineering, the role will model the relationship between AI developer tooling, internal token spend, and headcount; assess the end-to-end costs of AI-enabled engineering, including effects on cloud spend; and help optimize investments.

The role will lead multi-year headcount planning across global engineering hubs, balancing hiring costs, talent density, and university recruiting pipelines. It will also coordinate R&D hiring plans with Workplace and Facilities leaders' real estate strategy and multi-year CapEx planning.

The Director will scale R&D finance operations through automated workflows for headcount management, purchase-order planning, monthly accruals, and SOX audit compliance. They will use the Databricks platform to modernize internal finance tools and provide engineering leaders with self-service operational visibility. The position also builds, mentors, and scales a finance team responsible for both strategic capital allocation and operational execution.

Requirements

• 10+ years of experience in Strategic/Product Finance or R&D FP&A.
• Deep experience managing large-scale R&D OpEx, headcount capacity modeling, and multi-site workforce planning within a high-growth enterprise software or cloud company.
• Proven experience 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, including headcount tracking, procurement, close, and SOX controls, to support rapid scale.
• Experience building, leading, and developing high-output finance teams in fast-moving environments.

Nice To Haves

• Direct experience analyzing cloud dev/test infrastructure and AI tooling/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 deliver self-serve insights from large operational datasets.

Responsibilities

• Establish frameworks to measure product-level ROI and operationalize metrics to guide product investment and resource allocation.
• Model the economics of AI developer tooling and internal token spend alongside headcount, including tradeoffs between human and compute capital.
• Measure the end-to-end cost of AI-enabled engineering, including its impact on cloud spend, and partner with Engineering to optimize investments.
• Drive multi-year headcount planning across global engineering hubs, considering cost per hire, talent density, and university recruiting pipelines.
• Partner with Workplace and Facilities leadership to align R&D hiring roadmaps with global real estate strategy and multi-year CapEx planning.
• Build scalable, automated R&D finance workflows for headcount management, PO planning, monthly accruals, and SOX audit compliance.
• Use the Databricks platform to modernize internal finance tooling and provide engineering leaders with self-serve operational visibility.
• Build, mentor, and scale a high-performing finance team capable of strategic capital allocation and rigorous operational execution.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed