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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** CVS Health - **Location:** United States - **Experience:** Expert - **Salary:** $83,430.0 - $203,940.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Airflow, Amazon Web Services, Cloud Computing, Code Review, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Synchronization, Relational Databases, Database Development, Distributed Computing Environment, Distributed Systems, Identity and Access Management, Python (Programming Language), PostgreSQL, MongoDB, Operational Data Store, Performance Tuning, Query Optimization, Cloud Services, Cloudera, Software Engineering, Data Streaming, Web Services, Database Optimization, Caching, Change Data Capture, Indexer, Event Driven Architecture, Kubernetes, Low Latency, Real Time Data, Apache Kafka, Data Management, Database Replication, Terraform, Data Pipelines, Serverless Computing, Microservices - **Published:** September 28, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9315f3e60bfa6075 ## About the Role * 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 experience. * Cloud certifications (AWS and/or GCP) preferred. EST coast hours preferred * Education Bachelor's degree, or equivalent experience (HS diploma + 4 years relevant experience) ## Description Senior Data Engineer 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. This role is responsible for developing and supporting data flows from UniVerse 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 UniVerse while providing scalable, near real-time access for APIs and services. What You Will Do * 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. ## Related Videos - [40 Minutes to Build a Serverless COVID-19 REST and GraphQL APIs](https://www.wearedevelopers.com/videos/208-40-minutes-to-build-a-serverless-covid-19-rest-and-graphql-apis) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [HTTP headers that make your website go faster](https://www.wearedevelopers.com/videos/1676-http-headers-that-make-your-website-go-faster) - [Fully Orchestrating Databricks from Airflow](https://www.wearedevelopers.com/videos/336-fully-orchestrating-databricks-from-airflow) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Scaling: from 0 to 20 million users](https://www.wearedevelopers.com/videos/676-scaling-from-0-to-20-million-users) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market)