Senior Data Engineer, Observability Engineering

CVS Health is a healthcare company focused on creating a more connected, convenient, and compassionate health experience. The Senior Data Engineer, Observability Engineering will design, build, and operate scalable Databricks-based data pipelines and products supporting enterprise observability, operational intelligence, and security analytics. The role also owns engineering excellence, data governance, reliability, performance optimization, and data platform best practices.

Responsibilities:

• 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

Requirements:

• 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, Databricks Asset Bundles, serverless SQL, performance optimization, and platform operations
• 3+ years of experience developing high-volume batch and streaming data solutions, implementing data quality controls, troubleshooting pipeline issues, and improving reliability, scalability, and operational efficiency
• 2+ years of experience collaborating with engineering teams, participating in code reviews, contributing to technical standards, applying cloud security and access management principles, and communicating technical solutions to both technical and non-technical stakeholders
• Bachelor's degree from an accredited university or equivalent work experience (High School Diploma/GED plus 4 years of relevant experience)
• Experience building Structured Streaming and near real-time ingestion solutions within Databricks or similar cloud-native data platforms
• Experience implementing Databricks governance capabilities, including Unity Catalog, storage credentials, external locations, catalog management, and access control frameworks
• Familiarity with OCSF or similar observability, cybersecurity, or security event normalization frameworks
• Experience implementing CI/CD pipelines for data engineering solutions using Databricks Asset Bundles, GitHub Actions, Azure DevOps, or equivalent automation frameworks
• Prior experience supporting observability, infrastructure, cybersecurity, logging, telemetry, or operational analytics platforms in large-scale enterprise environments