Senior GCP Data Engineer for Patient Safety Measure Engine
About The Position
We are seeking a highly skilled Senior GCP Data Engineer to join our Medicare Patient Safety Data Engineering team. In this role, you will be responsible for building and maintaining the cloud infrastructure, data pipelines, and deployment workflows that calculate measure ratings for the med adherence and avoidance measures. You will turn these results into reliable, production-grade services that support STARS ratings. Your work will span 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
- 3+ years of experience on the Medicare Patient Safety domain with hands-on experience in calculating measure rates for Med-adherence, Med-avoidance measures.
- 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.
- Experience enabling adoption of GenAI capabilities with production-ready deployment and governance patterns.
- 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 for calculating measure ratings.
- Develop reliable, production-grade services for measure ratings.
- Collaborate with data scientists, product owners, and business stakeholders to deliver scalable solutions.
- Move insights from development to production.
- Work across cloud data engineering on Google Cloud Platform, backend API development, and DevOps/container orchestration.
Benefits
- medical
- dental
- vision coverage
- paid time off
- retirement savings options
- wellness programs
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What This Job Offers
Job Type
Full-time
Career Level
Senior
