Product Finance Director, AI Products & GPU Investment Strategy

Posted 5 Days 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 finance strategy for AI products, including GPU supply and demand planning, cloud capacity procurement, product pricing, unit economics, margin analytics, KPI development, cost allocation, ROI analysis, and capital allocation. Partners with Engineering and Product executives, builds scalable financial systems, and develops a high-performing product finance team.
Summary Generated by Built In

(GAQ427R229)

 

About the role

AI is the defining platform shift of our generation, and Databricks is right at the center of it. We are looking for a Product Finance leader to scale the fastest growing part of our business with both speed and financial rigor. You will be the primary finance partner to our AI Engineering and Product leaders, with a mandate that spans the full arc of the AI business: planning GPU supply and demand across clouds, shaping how we price AI products, and building the unit economics that will define the margins of this category for years to come. 

 

The impact you will have

  • Plan the GPU supply and demand that powers the business
    • Establish a trusted, unified GPU demand plan across production inference, internal research, and new product bets so we invest ahead of growth without over-provisioning.
    • Drive capacity commitment and procurement strategies across major hyperscalers and emerging neoclouds, optimizing the mix of reserved, spot, and on-demand compute.
  • Own AI product economics and partner on pricing
    • Lead revenue and margin analytics across the AI product portfolio, turning raw consumption telemetry into a clear read on customer adoption, retention, and product profitability.
    • Model the end-to-end unit economics of AI products before they ship, partnering with Product and Pricing to design consumption structures that drive adoption while protecting gross margin targets.
  • Establish robust KPIs and operations to drive best-in-class execution
    • Partner with Engineering to define north star efficiency KPIs (e.g., GPU utilization, cost per token/query, serverless efficiency) and translate them into committed engineering roadmaps.
    • Run tight financial operations, from auditable multi-cloud cost allocation to automated reporting, giving product and engineering leaders real-time visibility into their economic goals.
  • Bring finance rigor to the biggest investment decisions
    • Design ROI and capital allocation frameworks to evaluate asymmetric bets—including frontier model research, internal compute clusters, and strategic partnerships.
    • Build, mentor, and scale a high-performing team of product finance analysts capable of operating at the intersection of deep technical infrastructure and commercial strategy
What we look for

Required

  • 10+ years of experience in Strategic/Product Finance, complemented by foundational training in Investment Banking, Private Equity, or Management Consulting.
  • Deep fluency in consumption-based business models, public cloud infrastructure costs, unit cost analysis, and gross margin optimization.
  • A proven track record of partnering directly with senior Engineering and Product executives to influence technical roadmaps and commercial pricing.
  • Demonstrated ability to build scalable financial systems from scratch and distill massive, complex telemetry data into models and recommendations leaders act on.
  • Experience building, leading, and developing high-output finance teams in fast-moving environments.

 

Preferred

  • Direct experience operating in the AI and GPU economy, including familiarity with training/inference workloads, hyperscaler commitment structures, and neocloud economics.
  • Ownership of a multi-product P&L within a high-growth enterprise SaaS, PaaS, or data infrastructure company.
  • Hands-on proficiency with SQL, Python, or notebook environments to self-serve insights from raw usage data.

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 Finance or Product Finance
  • Foundational training in Investment Banking, Private Equity, or Management Consulting
  • Deep fluency in consumption-based business models, public cloud infrastructure costs, unit cost analysis, and gross margin optimization
  • Experience partnering directly with senior Engineering and Product executives to influence technical roadmaps and commercial pricing
  • Track record of building scalable financial systems and converting complex telemetry data into actionable models and recommendations
  • Experience building, leading, and developing high-output finance teams in fast-moving environments
  • Direct experience with AI and GPU economics, including training and inference workloads, hyperscaler commitments, and neocloud economics
  • Ownership of a multi-product P&L within a high-growth enterprise SaaS, PaaS, or data infrastructure company
  • Hands-on proficiency with SQL, Python, or notebook environments for analyzing raw usage data

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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