Senior Data Engineer (Requiring GCP)

CVS Health•Farmers Branch, TX

23h•$92,700 - $203,940•Onsite

About The Position

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. We seek a highly skilled Senior Cloud Engineer to join our Medicare Member Experience (MX) data science team. In this role, you will build and maintain the cloud infrastructure, data pipelines, and deployment workflows that turn our team's machine learning models into reliable, production-grade services that support STARS ratings. You will work across three key areas: cloud data engineering on Google Cloud Platform, backend API development, and DevOps/container orchestration. You will collaborate with data scientists, product owners, and business stakeholders to deliver scalable, well-architected solutions that move insights from development to production.

Requirements

4+ years of industry experience in cloud engineering, data engineering, or platform engineering.
Hands-on experience with Google Cloud Platform services (BigQuery, Composer/Airflow, Dataproc, Cloud Storage).
Experience building and deploying backend APIs and cloud-native services.
Solid expertise with containerization and orchestration (Docker, Kubernetes, GKE).
Proficiency in Python for data processing, orchestration, or backend services.
Strong SQL skills, particularly with BigQuery or similar cloud data warehouses.
Experience building and operating data pipelines and ETL/ELT workflows in a production environment.
Experience building and maintaining CI/CD pipelines (e.g., GitHub Actions, Jenkins), including automated testing and environment promotion.
Understanding of infrastructure-as-code, cloud reliability, and production incident response.
Self-directed problem solver willing to read documentation, research solutions, and reach out across teams to drive results.
Strong communication skills, including the ability to explain technical concepts to non-technical stakeholders.
Bachelor's degree in computer science, engineering, or related field.

Nice To Haves

Experience with Vertex AI (pipelines, model deployment, batch/online inference, or GenAI integration).
Practical MLOps experience, including model serving, monitoring, and retraining workflows.
Experience with distributed data processing frameworks such as Apache Spark or Apache Beam (Dataproc, Dataflow).
Experience with Cloud SQL/PostgreSQL and performance optimization for analytical serving patterns.
Familiarity with healthcare or insurance data ecosystems, or other regulated environments.
Experience improving platform reliability through observability, documentation, and operational playbooks.
Experience optimizing cloud infrastructure for cost, performance, and resiliency.
Experience building internal tools or product-facing analytics applications.
Advanced degree in computer science, engineering, or related field.

Responsibilities

Build and maintain cloud infrastructure, data pipelines, and deployment workflows.
Turn machine learning models into reliable, production-grade services.
Cloud data engineering on Google Cloud Platform.
Backend API development.
DevOps/container orchestration.
Collaborate with data scientists, product owners, and business stakeholders.
Deliver scalable, well-architected solutions.
Enable adoption of GenAI capabilities with production-ready deployment and governance patterns.