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

Posted 2 Hours Ago
Be an Early Applicant
3 Locations
In-Office
224K-308K Annually
Expert/Leader
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
Leads R&D product finance, capital allocation, ROI measurement, engineering economics, workforce and location planning, and finance operations. Partners with Engineering, Product Operations, People, Workplace, and Facilities executives to optimize human and compute capital investments. Builds scalable financial workflows, supports procurement, accruals, headcount planning, and SOX compliance, modernizes reporting using Databricks, and develops a high-performing finance team.
Summary Generated by Built In

(GAQ427R231)

 

About the role 

As Databricks scales at unprecedented velocity, how we invest our R&D capital—both human and compute—is critical to our scale. We are looking for a Product Finance leader to own R&D capital allocation and engineering operations. You will be a key finance partner to our senior Engineering and Product Operations leaders, with a mandate that spans product-level R&D ROI, global workforce and location strategy, and the rapidly evolving economics of AI-enabled software development.

The impact you will have

  • Drive product-level ROI and R&D capital allocation
    • Establish frameworks to measure product-level ROI across a fast-moving platform like Databricks where engineering velocity is extremely high.
    • Operationalize ROI metrics so they directly inform product investment and resource allocation decisions.
  • Define engineering economics in the AI era
    • 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 the second-order impact on cloud spend, and partner with Engineering to optimize investments.
  • Shape global workforce and location strategy
    • Drive multi-year headcount planning across global engineering hubs, balancing cost per hire, talent density, and university recruiting pipelines.
    • Partner closely with Workplace and Facilities leadership to synchronize R&D hiring roadmaps with global real estate strategy and multi-year CapEx planning.
  • Scale R&D finance operations and build the team
    • Bring systems-level thinking to R&D finance operations, building scalable, automated workflows across headcount management, PO planning, monthly accruals, and SOX audit compliance.
    • Dogfood the Databricks platform to modernize internal finance tooling and deliver self-serve operational visibility to engineering leaders.
    • Build, mentor, and scale a high-performing team of finance professionals capable of operating seamlessly across strategic capital allocation and rigorous operational execution.

What we look for

  • Required
    • 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.
    • 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 thinker with a demonstrated ability to re-engineer financial processes from scratch—spanning headcount tracking, procurement, close, and SOX controls—to support rapid scale.
    • Experience building, leading, and developing high-output finance teams in fast-moving environments.
  • Preferred
    • 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 self-serve insights from large operational datasets.

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 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 anticipates 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
$223,800—$307,650 USD

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 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 anticipates 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 2 Pay Range
$201,400—$276,850 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

  • 10+ years of experience in Strategic/Product Finance or R&D FP&A
  • Experience managing large-scale R&D OpEx, headcount capacity modeling, and multi-site workforce planning within a high-growth enterprise software or cloud company
  • Experience partnering directly with senior Engineering, Product Operations, and People/Workplace executives on capital allocation and operational rigor
  • Systems-level experience re-engineering financial processes spanning headcount tracking, procurement, close, and SOX controls
  • Experience building, leading, and developing high-output finance teams in fast-moving environments
  • 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 generate self-service insights

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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