Senior Data Engineer, Fleet Monitoring & Analysis
About the role
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.
Responsibilities
- Own and evolve the data lake and analytics stack that powers observability and decision-making for CoreWeave’s global hardware fleet.
- 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.
- 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.
Requirements
- 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.
Preferred Experience
- With modern data lake and lakehouse architectures and enjoying working with open-source data tooling.
- Expert at turning loosely defined business questions into concrete data products, metrics, and dashboards that drive decisions.
- 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.
Benefits
- Medical, dental, and vision insurance - 100% paid for by CoreWeave.
- Company-paid Life Insurance.
- Voluntary supplemental life insurance.
- Short and long-term disability insurance.
- Flexible Spending Account (FSA) and Health Savings Account (HSA).
- Tuition Reimbursement.
- Ability to participate in Employee Stock Purchase Program (ESPP).
- Mental Wellness Benefits through Spring Health.
- Family-Forming support provided by Carrot.
- Paid Parental Leave.
- Flexible, full-service childcare support with Kinside.
- 401(k) with a generous employer match.
- Flexible PTO.
- Catered lunch each day in our office and data center locations.
- A casual work environment.
- A work culture focused on innovative disruption.
Pay
The base salary range for this role is $153,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation.
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