Senior Data Engineer (Fleet Monitoring & Analysis)

Join CoreWeave, a leading cloud provider specializing in GPU-accelerated computing. As a Senior Data Engineer, you will own and evolve the data lake and analytics stack that powers observability and decision-making for our global hardware fleet. You will maintain, monitor, and upgrade our data lake infrastructure, ETL pipelines, and deliver ad-hoc analysis and executive-ready reporting. You will also create visualizations, documentation, and integrations to make fleet monitoring data reliable, discoverable, and actionable across the organization.

• Conception, développement et maintenance de pipelines de données robustes et évolutifs pour collecter, traiter et stocker des données provenant de diverses sources.
• Surveillance, mise à niveau et amélioration de l'infrastructure du lac de données de CoreWeave, y compris Apache Iceberg, la couche de requête Trino, Apache Airflow, Apache Spark et Apache Superset.
• Création et optimisation de modèles de données et de produits de données pour soutenir l'analyse et le reporting, en garantissant l'exactitude, la cohérence et la performance des données.
• 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
• Experience creating and maintaining reporting and analytics solutions (dashboards, reports, and metrics) for technical and non-technical audiences
• Strong SQL skills for data manipulation, modeling, and querying large datasets
• Experience designing, operating, and optimizing data lake and/or data warehouse solutions, with a solid understanding of data modeling and performance tuning
• Experience building, maintaining, and monitoring ETL/ELT pipelines in production environments, including alerting and observability
• Familiarity with database systems (e.g., SQL and NoSQL) and data warehousing concepts, including partitioning, indexing, and schema design
• Bachelor’s degree in Computer Science, Engineering, or a related field
• Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and related data services (e.g., object storage, managed databases, analytics services)
• Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and big data technologies (e.g., Apache Spark)
• 4 - 7 years of experience as a Data Engineer or in a similar data-focused role in a fast-paced environment
• Proficiency in at least one programming language commonly used for data engineering such as Python, Java, or Scala
• Experience with Apache Superset or other BI/visualization tools for building self-service analytics
• Experience with modern data lakehouse technologies and table formats such as Apache Iceberg (or similar technologies like Delta Lake or Apache Hudi)
• Experience with Trino or other distributed SQL query engines at scale
• 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
• Experience with data quality frameworks, data observability tooling, and/or metadata management
• Experience supporting executive-level reporting and KPI design in partnership with business and finance stakeholders
• You love owning data infrastructure end-to-end—from ingestion and modeling to analytics and visualization
• You’re an expert at turning loosely defined business questions into concrete data products, metrics, and dashboards that drive decisions
• You’re curious about modern data lake and lakehouse architectures and enjoy working with open-source data tooling