Senior Data Engineer - PostgreSQL and MongoDB

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.

Senior Data Engineer - PostgreSQL and MongoDBwill 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 Uni Verse environment. This role is responsible for developing and supporting data flows from Uni Verse through CDC replication into PostgreSQL, transformation and enrichment processes on GCP, and delivery of optimized data models within MongoDB Atlas.

The ideal candidate will possess strong expertise in operational data platforms, CDC technologies, data replication, PostgreSQL, MongoDB, and cloud-native data engineering. This individual will contribute to the design, implementation, performance optimization, reliability, and operational support of the transactional cache ecosystem. The platform is intended to reduce transactional workloads on Uni Verse while providing scalable, near real-time access for APIs and services.

• 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 Uni Verse 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.

• 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.

• Experience implementing transactional cache or operational data platform architectures.
• Kafka, Pub/Sub, or event-driven architecture experience.
• Experience building data platforms that support APIs and microservices.
• Terraform or Infrastructure as Code experience.
• Experience with GKE/Kubernetes.
• Experience designing highly available and low-latency data platforms.
• Agile/SAFe experience in large enterprises.
• Healthcare industry experience.
• AWS…