Senior Data Engineer

About the Role Senior Data Engineer will own and evolve the data lake and analytics stack that powers observability and decision-making for CoreWeave’s global hardware fleet. You will maintain, monitor, and upgrade our data lake infrastructure and ETL pipelines, while delivering ad-hoc analysis and executive-ready reporting. You’ll also create visualizations, documentation, and integrations that make fleet monitoring data reliable, discoverable, and actionable across the organization.

What You'll Do

• 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.

What We're Looking For

• 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.

Nice to Have

• 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.
• Experience with Apache Superset or other BI/visualization tools for building self-service analytics.
• 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.

Compensation & Benefits

• The base salary range for this role is USD 153,000 to USD 204,000 per year. Our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).