Senior Data Engineer

We're building a world of health around every individual , shaping a more connected, convenient and compassionate health experience.

As a Senior Data Engineer at CVS Health, you will design, build, and support a near real-time transactional cache platform that enables APIs, digital experiences, and downstream services to consume operational data outside of the legacy UniVerse environment.

Responsibilities

• Design, develop, and support a near real-time transactional cache platform supporting APIs, applications, and digital experiences.
• Build and maintain Change Data Capture (CDC) pipelines that replicate data from UniVerse into PostgreSQL using vendor-supported replication technologies.
• Develop and support transformation pipelines that convert operational relational data into optimized MongoDB document structures.
• Implement and support MongoDB document models, indexing strategies, partitioning approaches, and query patterns to support high-throughput, low-latency API consumption.
• Partner with API and application development teams to define and deliver cache-ready domain models that meet performance and scalability requirements.
• Monitor and improve data freshness, latency, availability, and reliability of transactional cache workloads.
• Optimize PostgreSQL and MongoDB performance through schema design, indexing, query tuning, and capacity planning.
• Troubleshoot production issues and participate in operational support, incident response, and root cause analysis activities.
• Develop and maintain operational runbooks, monitoring dashboards, alerting strategies, and support procedures.
• Collaborate with architects, senior engineers, and cross-functional teams to implement scalable and maintainable data platform solutions.
• Contribute to engineering best practices, code reviews, documentation, and continuous improvement initiatives.
• Mentor junior engineers and share knowledge related to CDC, data pipelines, and cloud-native data engineering practices.

Requirements

• 5+ years of data engineering, software engineering, or data platform development experience.
• 3+ years designing, developing, and supporting enterprise-scale data platforms and distributed systems.
• Strong MongoDB Atlas /PostgreSQL experience including data modeling, aggregation frameworks, index design, and performance optimization.
• Experience with Change Data Capture (CDC), replication technologies, and near real-time data movement patterns.
• Experience designing and supporting operational data stores, transactional caches, or API-serving data platforms.
• Strong Python and SQL development skills.
• Experience with GCP services including Cloud SQL, Dataproc Serverless, Cloud Composer (Airflow), Monitoring, IAM, and cloud networking fundamentals.
• Experience developing and supporting production ETL/ELT pipelines.
• Experience working in Linux/Unix environments.
• Ability to troubleshoot distributed data processing and data synchronization issues.
• Strong problem-solving, communication, and collaboration skills.

Benefits

• Medical, dental, and vision coverage
• Paid time off
• Retirement savings options
• Wellness programs
• Other resources, based on eligibility