Staff Product Manager, Data Services
CoreWeave
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.
What You’ll Do:
The Data Services Team builds and operates the data platform that powers CoreWeave's AI cloud, from transactional and analytical storage to streaming, metadata, and governance. We give our customers and CoreWeave engineers the primitives they need to ingest, store, process, and serve data at the scale and performance that next-generation AI workloads demand.
If you want to define how data flows across a rapidly scaling AI cloud, and turn that strategy into infrastructure others depend on, this is your team.
About the role:
As a Staff Product Manager for Data Services, you'll own the end-to-end strategy, roadmap, and execution for CoreWeave's data services portfolio: databases, data lakes, streaming, metadata and catalog, and data sharing and integration.
You'll shape a multi-year vision for how our data services underpin AI and GPU workloads, then lead delivery from 0 to 1 and 1 toN. That means working directly with strategic customers and partners, collaborating closely with engineering and GTM, evaluating emerging data technologies, and ensuring our services are secure, reliable, and easy to adopt.
The hardest problems you'll tackle are around scale, throughput, and performance for GPU-intensive applications, and you'll have real influence over the architecture to solve them.
In this role, you will own:
- Product strategy and roadmap across the data services portfolio, balancing near-term delivery with long-term bets
- Customer and partner engagement - diving deep into data architectures, co-designing solutions, and supporting large-scale deployments
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