Senior Data Engineer - Real-Time CDC, MongoDB & PostgreSQL

CVS Health; United States; Remote; USD 83,000 - 204,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

Paid time off

Retirement savings options

Wellness programs

Job summary

CVS Health is advancing a near real-time data platform to empower APIs and digital experiences. The Senior Data Engineer will design, build, and operate CDC pipelines from UniVerse to PostgreSQL, transform data for MongoDB Atlas, and optimize workloads in a cloud-native environment.

You’ll partner with API teams to deliver scalable cache-ready models and maintain data freshness across systems. You will design data models, implement indexing strategies, and monitor latency while collaborating

Qualifications

• 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.

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.

Skills

Python

SQL

Data engineering

Distributed systems

Linux/Unix

Problem solving

Communication

Collaboration

Education

Bachelor’s degree or equivalent

Tools

MongoDB Atlas

PostgreSQL

Airflow

Cloud SQL

Dataproc Serverless

Cloud Composer

GKE/Kubernetes

Terraform

Pub/Sub

Kafka

Job description

CVS Health is advancing a near real-time data platform to empower APIs and digital experiences. The Senior Data Engineer will design, build, and operate CDC pipelines from UniVerse to PostgreSQL, transform data for MongoDB Atlas, and optimize workloads in a cloud-native environment.

You’ll partner with API teams to deliver scalable cache-ready models and maintain data freshness across systems. You will design data models, implement indexing strategies, and monitor latency while collaborating