Product Finance Senior Manager, Cloud Platform Costs & Operations
- Pay
- $216,100 – $297,100 per year
- Location
- Mountain View, CA
- Job type
- Full-time
- Level
- Director
- Experience
- 8+ years
- Listed
- 23 days ago
Skills & highlights for this role
- cloud cost forecasting
- driver-based financial modeling
- unit economics analysis
- public cloud cost analysis (AWS, Azure, GCP)
Also useful
- SQL
- Python
- Databricks
Stated benefits & perks
- Annual performance bonus
- Equity
(Gaq427r230)
About the role As customers build their mission-critical data and AI workloads on Databricks, our shared cloud platform infrastructure is scaling at unprecedented speed. We are looking for a Product Finance Senior Manager to own the economics and financial operations of our multi-cloud platform spend. You will be a key finance partner to our Cloud Engineering and Infrastructure Operations leaders, with a mandate that spans driver-based cloud forecasting, infrastructure efficiency roadmaps, and scalable cost attribution across our product portfolio.
The impact you will have
- Drive analytics and modeling to understand how platform spend scales
- Lead deep data analytics to identify the underlying drivers of shared cloud platform spend across products, cloud providers, and global regions.
- Build robust, driver-based forecasting models that accurately predict infrastructure spend across regional expansion, customer scale, and new product launches.
- Partner with Cloud Infrastructure Operations to design a forward-looking cost attribution model that accurately maps shared platform expenses to individual products.
- Establish robust KPIs and operations to achieve unit economics goals
- Partner with Engineering to define north star efficiency KPIs across core platform services and storage/compute layers.
- Build the infrastructure efficiency roadmap alongside Engineering and translate technical optimizations into committed operating and gross margin targets.
- Drive tight operational rhythms and reporting so product and engineering leaders have clear visibility to execute against their unit economic goals.
- Scale cloud finance operations and systems
- Bring systems-level thinking to cloud FP&A processes, building automated workflows that scale as our multi-cloud footprint and commitment structures become increasingly dynamic.
- Ensure cloud cost allocation frameworks, monthly accruals, and reporting pipelines remain rigorous, auditable, and scalable as the business compounds.
- Dogfood the Databricks platform to analyze massive cloud billing and telemetry datasets, delivering self-serve cost visibility to engineering partners.
What we look for
- Required
- 8+ years of experience in Strategic/Product Finance, Cloud FP&A, or FinOps, complemented by foundational training in Investment Banking, Consulting, or high-growth technology.
- Deep fluency in consumption-based business models, public cloud infrastructure costs (AWS, Azure, GCP), unit cost analysis, and gross margin drivers.
- A proven track record of partnering directly with Engineering and Cloud Infrastructure Operations teams to drive cost efficiency and forecasting accuracy.
- Systems-level thinker with a demonstrated ability to build scalable financial processes, driver-based models, and auditable allocation frameworks in fast-moving environments.
- Preferred
- Functional expertise in hyperscaler cloud pricing, enterprise commitment structures, and infrastructure deal economics.
- Experience attributing shared platform or foundational infrastructure costs across a multi-product SaaS or PaaS portfolio.
- Hands-on proficiency with SQL, Python, or notebook environments (especially Databricks) to self-serve insights from massive cloud billing and usage 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 $216,100—$297,100 USD
Pay Range Transparency
Zone 2 Pay Range $194,500—$267,400 USD
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
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.
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.
Equal opportunity and legal notices
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.
From Databricks's careers page, first listed on Rolev.ai on October 17, 2026. Rolev.ai is not the employer.
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Common questions
What is the salary for the Product Finance Senior Manager, Cloud Platform Costs & Operations role at Databricks?
The Product Finance Senior Manager, Cloud Platform Costs & Operations posting at Databricks states compensation of $216,100 – $297,100 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on Databricks's official career site.
Where is the Product Finance Senior Manager, Cloud Platform Costs & Operations job at Databricks located?
This Product Finance Senior Manager, Cloud Platform Costs & Operations position at Databricks is located in Mountain View, CA. Always check Databricks's application page for specific state eligibility or relocation policies.
What qualifications are required for Product Finance Senior Manager, Cloud Platform Costs & Operations at Databricks?
For the Product Finance Senior Manager, Cloud Platform Costs & Operations role, Databricks highlights 8+ years of relevant experience; experience with cloud cost forecasting, driver-based financial modeling, unit economics analysis, public cloud cost analysis (AWS, Azure, GCP). Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Product Finance Senior Manager, Cloud Platform Costs & Operations position at Databricks?
This listing links directly to Databricks's Greenhouse application page. You can apply directly on Databricks's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Greenhouse application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.