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CVS Health logo

Staff Data Engineer, Observability Data Lake

CVS Health · TX - Work from home · Posted 44 days ago

$118k–$237kRemoteic
7+ yrs expDatabricksPythonPySparkSQLSparkDelta LakeData EngineeringStructured Streaming

POSITION SUMMARY CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Staff Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Staff Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Staff Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patterns. The ideal candidate is passionate about engineering high-quality solutions, proactively identifying opportunities for improvement, influencing technical standards, and raising the overall quality, reliability, and maintainability of the platform and team.

PRIMARY RESPONSIBILITIES

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There are 37,231 open roles at CVS Health right now. This role is one of 47 Data Engineer openings in Remote and centers on Databricks, Python, Pyspark, and SQL.

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