Senior Data Engineer, CoreWeave

• Bachelor’s degree in Computer Science, Engineering, or a related field
• 4 - 7 years of experience as a Data Engineer or in a similar data-focused role in a fast-paced environment
• Strong SQL skills for data manipulation, modeling, and querying large datasets
• Proficiency in at least one programming language commonly used for data engineering such as Python, Java, or Scala
• Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and big data technologies (e.g., Apache Spark)
• Experience designing, operating, and optimizing data lake and/or data warehouse solutions, with a solid understanding of data modeling and performance tuning
• Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and related data services (e.g., object storage, managed databases, analytics services)
• Familiarity with database systems (e.g., SQL and NoSQL) and data warehousing concepts, including partitioning, indexing, and schema design
• Experience building, maintaining, and monitoring ETL/ELT pipelines in production environments, including alerting and observability
• Experience creating and maintaining reporting and analytics solutions (dashboards, reports, and metrics) for technical and non-technical audiences
• 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 owning data infrastructure end-to-end—from ingestion and modeling to analytics and visualization
• You’re curious about modern data lake and lakehouse architectures and enjoy working with open-source data tooling
• You’re an expert at turning loosely defined business questions into concrete data products, metrics, and dashboards that drive decisions
• This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency

Desirable

• The Fleet Monitoring and Analysis (FMA) team builds and operates the forward-deployed monitoring and observability layer for CoreWeave’s ever-expanding global hardware fleet; continually improving node and environmental visibility to support automated provisioning and high-reliability operations
• As a Senior Data Engineer you will own and evolve the data lake and analytics stack that powers observability and decision-making for CoreWeave’s global hardware fleet
• You’ll maintain, monitor, and upgrade our data lake infrastructure (Apache Iceberg, Trino, Apache Airflow, Apache Spark, Apache Superset) and ETL pipelines, while delivering ad-hoc analysis and executive-ready reporting for team, director, and leadership stakeholders
• You’ll also create visualizations, documentation, and integrations that make fleet monitoring data reliable, discoverable, and actionable across the organization
• Design, develop, and maintain robust and scalable data pipelines to collect, process, and store data from various sources, including APIs, databases, and third-party services
• Maintain, monitor, and upgrade CoreWeave’s data lake infrastructure, including Apache Iceberg, the Trino query layer, Apache Airflow, Apache Spark, and Apache Superset
• Maintain, monitor, and upgrade ETL/ELT pipelines to ensure reliable, performant, and observable data flows across batch and (where applicable) streaming workloads
• Create and optimize data models and data products to support analytics and reporting, ensuring data accuracy, consistency, and performance
• Provide ad-hoc analysis and reporting for team, director, and executive-level stakeholders, translating business questions into data-driven insights and clear narratives
• Create visualizations and dashboards (e.g., in Apache Superset or similar tools) that surface key metrics, trends, and operational KPIs for a variety of internal audiences
• Develop and maintain documentation and runbooks for data pipelines, data lake infrastructure, data models, and usage patterns to support knowledge sharing and troubleshooting
• Implement data security and governance best practices to protect sensitive information and comply with data privacy regulations
• Collaborate with cross-functional teams to integrate data into applications and analytics platforms, helping to visualize performance metrics and identify opportunities for improvement