Data Engineer

CVS Health is a leading healthcare company dedicated to simplifying health care for individuals and communities. The Data Engineer role involves designing, developing, and maintaining data pipelines to manage large healthcare datasets, ensuring compliance and optimizing data models to support business decisions.

Responsibilities

• Build and optimize analytical data models in BigQuery. Implement partitioning, clustering, and materialized views for performance and cost efficiency. Ensure compliance with data governance, access controls, and IAM best practices
• Develop integrations with external systems (APIs, flat files etc.) using GCP-native or hybrid approaches. Utilize tools like Dataflow or custom Python/Java services on Cloud Functions or Cloud Run to handle transformations and ingestion logic
• Build automated CI/CD pipeline using Cloud Build, GitHub Actions, or Jenkins for deploying data pipeline code and workflows. Set up observability using Cloud Monitoring, Cloud Logging, and Error Reporting to ensure pipeline reliability

Skills

• 1+ years of experience with SQL, NoSQL
• 1+ years of experience with Python (or a comparable scripting language)
• 1+ years of experience with Data warehouses (such as data modeling and technical architectures) and infrastructure components
• 1+ years of experience with ETL/ELT, and building high-volume data pipelines
• 1+ years of experience with reporting/analytic tools
• 1+ years of experience with query optimization, data structures, transformation, metadata, dependency, and workload management
• 1+ years of experience with Big data and cloud architecture
• 1+ years of hands-on experience building modern data pipelines within a major cloud platform (GCP)
• 1+ years of experience with deployment/scaling of apps on containerized environment (i.e. Kubernetes, AKS)
• 1+ years of experience with real-time and streaming technology (i.e. Kafka, Spark Streaming)
• 1+ year(s) of soliciting complex requirements and managing relationships with key stakeholders
• Experience with complex systems and solving challenging analytical problems
• Strong collaboration and communication skills within and across teams
• Knowledge of data visualization and reporting
• Experience in designing and building data engineering solutions in cloud environments (preferably GCP)
• Experience with Git, CI/CD pipeline, and other DevOps principles/best practices
• Experience with bash shell scripts, UNIX utilities & UNIX Commands
• Understanding of software development methodologies including waterfall and agile
• Ability to leverage multiple tools and programming languages to analyze and manipulate data sets from disparate data sources
• Knowledge of API development
• Experience with schema design and dimensional data modeling
• Google Professional Data Engineer Certification
• Knowledge of microservices and SOA
• Formal SAFe and/or agile experience. Previous healthcare experience and domain knowledge
• Experience designing, building, and maintaining data processing systems
• Experience architecting and building data warehouse and data lakes

Benefits

• Medical, dental, and vision coverage
• Paid time off
• Retirement savings options
• Wellness programs
• Other resources, based on eligibility

Company Overview

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