Product Finance Senior Manager, Cloud Platform Costs & Operations
Databricks · Mountain View, California; San Francisco, California; Seattle, Washington · Finance · listed October 16, 2026
The shape of it
Seniority
Manager
Experience asked
8+ years
Where
Not stated
Stated pay
$216,100 – $297,100 USD
Requirements listed
9
Length
912 words
In the posting’s own words
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.
What it asks for · 9
- 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.
What the job covers
- 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.
Tools and skills named
Go to market
- Forecasting3×
- SaaS
Cloud & infra
- AWS
- Azure
- GCP
Data
- Databricks3×
Languages
- Python
- SQL
Product & design
- Roadmap
Words the posting leans on
- cloud15×
- infrastructure10×
- cost8×
- platform8×
- engineering6×
- operations6×
- product6×
- build4×
- economics4×
- efficiency4×
- finance4×
- models4×
- partner4×
- scale4×
- shared4×
- cloud infrastructure3×
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