The posting, in CoreWeave's own words
archived Sep 9, 2026CoreWeave 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 Engineering Team builds and operates the foundational data infrastructure powering analytics, AI, and operational decision-making across CoreWeave. We design resilient data pipelines, scalable lakehouse systems, and high-quality datasets that enable teams across Finance, HR, Operations, and Engineering to move faster and make smarter decisions. Our mission is to make CoreWeave's data reliable, accessible, and actionable at scale.
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About the role:
We're seeking a Senior Data Engineer to design and build the foundational datasets that power analytics, business intelligence, and AI across CoreWeave. You will own the development of dimensional data models, enterprise metrics, and curated data products that enable analysts, data scientists, and business stakeholders to answer complex questions with confidence. Day-to-day, you'll partner closely with business domains and analytics teams to translate operational processes into scalable data models while ensuring performance, quality, and consistency across the data ecosystem. This role combines deep data modeling expertise with strong software engineering skills across our modern lakehouse platform.
Who You Are:
Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent experience) 5+ years of experience designing and building analytical data models in enterprise data warehouse or lakehouse environments. Expertise in at least one programming language such as Python, Scala, or Rust, with experience building production-grade data systems. Advanced SQL skills with demonstrated experience developing, optimizing, and troubleshooting complex analytical workloads. Hands-on experience building and operating distributed data processing systems using Spark, Flink, or similar technologies. Experience working with modern lakehouse architectures and analytical technologies such as Iceberg, Delta, StarRocks, Clickhouse, or Trino. Deep expertise applying dimensional modeling techniques to scaled OLAP workloads. Strong experience building curated datasets, semantic models, and enterprise metrics that support business intelligence, advanced analytics, and AI use cases.