Senior Data Engineer

About the role

CoreWeave is seeking a Senior Data Engineer to design and maintain high-performance data pipelines that support our AI-native cloud infrastructure. You will work on the systems that power large-scale GPU compute, storage, and networking services for complex AI workloads. In this capacity, you will own the architecture of critical data ingestion and distribution systems that ensure timely and accurate insights across the organization. You will be responsible for translating complex operational telemetry into reliable data products that drive decision-making for AI infrastructure teams. The role requires a deep commitment to building robust, scalable, and observable data solutions that meet the demands of high-velocity environments. You will partner closely with cross-functional engineering groups to align data strategies with evolving business and technical objectives. Your work will directly influence the reliability and performance of the platforms that power AI model training and inference. This position is ideal for a hands-on technical leader who thrives on solving complex data challenges at scale.

Key facts

What you'll do

• Architect and build scalable data infrastructure to handle high-volume telemetry and operational metrics from our GPU clusters.
• Collaborate with engineering teams to optimize data flow for AI model training and inference platforms.
• Develop automated processes for data ingestion, transformation, and storage to ensure reliability and performance.
• Maintain data quality and accessibility for internal stakeholders monitoring fleet lifecycle and observability metrics.
• Design and implement data models that support analytics, monitoring, and operational intelligence across distributed systems.
• Partner with data scientists and platform engineers to deliver data-driven solutions that enhance AI workload performance.
• Implement monitoring and alerting for data pipelines to ensure high availability and rapid issue resolution.
• Evaluate and integrate new data technologies to improve scalability, efficiency, and maintainability of the data platform.
• Lead technical design discussions and code reviews to uphold engineering best practices and standards.
• Contribute to the development of data governance policies to ensure compliance and data integrity.
• Collaborate with security teams to implement data protection measures and access controls.
• Support the deployment and operation of data pipelines in production environments using CI/CD methodologies.
• Analyze system performance metrics to identify bottlenecks and drive optimization initiatives.
• Document data architectures, pipelines, and processes to ensure clarity and knowledge transfer across teams.

Requirements

• Proven experience in designing and managing large-scale data pipelines in a cloud environment.
• Proficiency in building and maintaining distributed systems.
• Strong background in data architecture, modeling, and storage solutions.
• Ability to work effectively within a fast-paced environment focused on AI infrastructure.
• Demonstrated expertise in data engineering frameworks and distributed computing technologies.
• Experience with cloud-native infrastructure and observability tools is essential.
• Familiarity with GPU-accelerated computing environments and AI workloads is highly relevant.
• Strong understanding of data governance, security, and compliance principles.
• Excellent problem-solving skills and the ability to debug complex data issues.
• Effective communication skills to collaborate with technical and non-technical stakeholders.
• A proactive mindset with the ability to learn new technologies and adapt to changing requirements.
• Commitment to writing clean, maintainable, and efficient code.
• Willingness to participate in on-call rotations to support critical data infrastructure.

Skills & tools

• Expertise in data engineering frameworks and distributed computing.
• Experience with cloud-native infrastructure and observability tools.
• Familiarity with GPU-accelerated computing environments and AI workloads.
• Strong proficiency in data modeling, ETL processes, and database systems.
• Experience with containerization and orchestration platforms used in cloud environments.
• Knowledge of monitoring and logging tools for distributed systems.
• Understanding of data streaming technologies and real-time processing systems.
• Familiarity with infrastructure-as-code practices for data platform management.
• Experience with version control and collaborative development workflows.
• Ability to work with both batch and stream processing workloads.

Practical notes

CoreWeave is an AI-native cloud provider specializing in high-performance GPU infrastructure for training and inference. Please submit your application via the company career portal.

The role of is centered on building and sustaining the data backbone that powers AI innovation. The successful candidate will be deeply involved in every stage of the data lifecycle, from ingestion and processing to optimization and governance. This position demands a balance of technical depth and cross-functional collaboration to ensure that data remains a strategic asset for the company. You will be expected to contribute not only through code but also through thoughtful design and clear documentation. The fast-paced nature of AI infrastructure requires adaptability and a continuous learning mindset. CoreWeave values engineers who take ownership of their work and drive initiatives forward with minimal supervision. This role offers the opportunity to work on impactful systems at the intersection of data engineering and artificial intelligence. It is suited for professionals who are passionate about building the foundational layers that enable next-generation AI applications. The position reflects CoreWeave's commitment to engineering excellence and innovation in cloud-based computing.