Senior Data Engineer, Observability Engineering

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

CVS Health is seeking a highly skilled Senior 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 Senior 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 Senior 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 Senior 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.

• Design, build, deploy, and support scalable Databricks-based data pipelines and lakehouse solutions that ingest, transform, and curate observability, infrastructure, and security data from multiple enterprise sources.

• Develop and optimize PySpark workloads, Structured Streaming jobs, and bronze/silver/gold data architectures while ensuring high performance, reliability, scalability, data quality, and operational excellence.

• Partner with Security, Infrastructure, Observability, and Platform Engineering teams to onboard new data sources, establish governance standards, improve metadata management, and deliver trusted enterprise data products.

• Contribute to engineering standards, code reviews, CI/CD practices, monitoring strategies, and platform optimization efforts while proactively identifying and addressing technical debt, process gaps, and operational risks.

• Support the ongoing evolution of the enterprise observability lakehouse by promoting best practices for Databricks, Delta Lake, Unity Catalog, data governance, security controls, access management, and cost‑efficient data platform operations.

• 5+ years of experience building and supporting enterprise data engineering solutions using Python, Spark, PySpark, SQL, and distributed data processing technologies.

• 5+ years of experience designing, developing, and operating large-scale data pipelines, data ingestion frameworks, and bronze/silver/gold lakehouse architectures across multiple data sources.

• 4+ years of experience working with Databricks in production environments, including Delta Lake, Unity Catalog,…