DataOps Engineer

Responsibilities

• Design and implement the end-to-end observability stack for data workloads across batch and streaming pipelines
• Define and maintain operational SLOs/SLAs for critical data flows
• Build dashboards, alerts, and runbooks for data incident remediation
• Deploy and maintain end-to-end data lineage for key domains
• Roll out data quality checks including schema, freshness, and drift
• Establish CI/CD patterns and infra-as-code for data pipelines
• Mentor engineering teams on resilient schemas and operational practices

Requirements

• 5–6+ years of experience in DataOps, Data Engineering, or DevOps/SRE
• Strong experience with data orchestration and ETL/ELT tooling (e.g., Airflow, Dagster, dbt)
• Solid SQL and/or Spark skills
• Experience with analytical databases or warehouses
• Proficiency in Python for building tooling and integrations
• Experience with containerized, cloud-native environments like Kubernetes
• Strong automation mindset with infra-as-code and CI/CD

Preferred Qualifications

• Experience in ML/AI platforms or MLOps environments
• Background with test, simulation, or time-series data
• Familiarity with feature stores, experiment tracking, or model registries
• Experience with multi-tenant SaaS platforms

About the Company

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence.