Staff Data Engineer - Data Engineering

About this role

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 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.

About the role:

We're seeking a Staff Data Engineer to define and drive the architecture of CoreWeave's enterprise data ecosystem. You will establish the modeling, semantic, governance, and platform standards that enable teams to build trusted and reusable data products at scale. Day-to-day, you'll lead cross-domain architecture, solve the organization's most complex data design challenges, and partner with senior engineers and stakeholders to translate business requirements into durable technical systems. This role combines deep hands-on engineering expertise with company-wide technical leadership across our modern lakehouse platform.

In this role, you will:

• Define the company-wide strategy for data modeling, semantic layers, enterprise metrics, and reusable data products.

• Set architectural standards for CoreWeave's lakehouse, including data organization, schemas, metadata, governance, and serving patterns.

• Design scalable frameworks for data quality, lineage, observability, access control, and policy enforcement.

• Lead the architecture of complex, cross-domain data systems spanning operational, financial, product, people, and infrastructure data.

• Establish durable data contracts, system boundaries, and reusable engineering patterns across teams.

• Identify and resolve systemic performance, reliability, and scalability constraints across the data ecosystem.

• Lead architecture reviews for high-impact initiatives and ensure alignment with the broader platform strategy.

• Evaluate and standardize core data technologies across processing, orchestration, cataloging, modeling, and metadata management.

• Mentor senior engineers and raise the quality of system design and technical decision-making across the organization.

Who You Are:

• 10+ years of experience in data engineering, software engineering, distributed systems, or data architecture roles.

• Demonstrated experience setting technical direction for data systems spanning multiple teams, business domains, or platforms.

• Deep expertise in enterprise analytical modeling, including dimensional, Data Vault, semantic modeling, and governed metrics.

• Experience designing and operating large-scale lakehouse or streamhouse architectures using technologies such as Apache Iceberg, Delta Lake, Apache Hudi, Apache Paimon, or Apache Fluss.

• Advanced knowledge of distributed OLAP, query, processing, and ingestion systems such as StarRocks, ClickHouse, Trino, Spark, Flink, or Kafka.

• Expert-level SQL and strong programming expertise in Python, Scala, Java, or Rust, with experience building production-grade data systems.

• Demonstrated experience implementing governance capabilities such as lineage, profiling, metadata management, data quality controls, access policies, or auditability.

• Demonstrated ability to independently turn ambiguous problem statements into clear technical direction and execution plans.

• Track record of leading cross-cutting architecture and establishing standards adopted across multiple engineering teams.

Preferred:

• Experience designing data systems that support compliance programs such as SOX, GDPR, MNPI, and PII controls.

• Experience operating event-driven architectures using Kafka, AutoMQ, Pulsar, or similar streaming platforms.

• Experience running data-intensive workloads on Kubernetes.

• Experience in high-growth cloud, infrastructure, or distributed-systems organizations.

Wondering if you're a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk.

• You love designing, implementing, and operating data platforms and distributed systems at extreme scale.

• You're energized by solving ambiguous, cross-domain technical problems and turning them into clear, durable solutions.

• You enjoy raising the quality of engineering through thoughtful architecture, standards, and mentorship.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core

• Act Like an Owner

• Empower Employees

• Deliver Best-in-Class Client Experiences

• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, t

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