Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data + AI Platform. Backed by Battery, Insight and Kleiner Perkins.
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. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 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
More about this role
(GAQ427R231)
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.
- 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...
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