Senior Data Engineer - AI and Analytics

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.

If you’re eager to make a real impact in the health care industry through your own meaningful contributions, explore a role in technology with CVS Health. Our journey calls for technical innovators and data visionaries: come help us pave the way.

At CVS Health, we possess an extensive repository of healthcare data that spans over 150 million individuals, providing an unparalleled foundation for ambitious Data Engineers. In this role, you will engage with complex business challenges, harnessing modern tools and technologies to securely store, process, transform, and enrich terabyte to petabyte scale healthcare data. Your work will underpin data-driven business decisions and contribute to our mission of delivering industry‑best data products / software with a customer‑first mindset and team‑oriented approach.

As a Senior Data Engineer, you will be instrumental in designing, developing, and maintaining optimal data pipelines to assemble large and intricate datasets, catering to the business requirements of various CVS lines of business. You will collaborate closely with teams, crafting tools to provide actionable insights and integrate them with consumer touchpoints.

As leaders in healthcare, our analytics and engineering teams deliver innovative solutions to business problems by collaborating with cross‑functional teams in a dynamic and agile environment. You will be part of a team that values collaboration and encourages innovative thinking at all levels. You will be intellectually challenged to solve problems associated with large scale complex, structured and unstructured data, allowing you to grow your technical skills and engineering expertise.

• 3‑5+ years of experience with SQL and No
  
  SQL
• 3‑5+ years of experience with Python
• 3+ years of experience with data warehouses such as data modeling and technical architectures, and infrastructure components
• 3+ years of experience with ETL/ELT, and building high‑volume data pipelines
• 3+ years of experience with reporting/analytic tools
• 3+ years of experience with query optimization, data structures, transformation, metadata, dependency, and workload management
• 3+ years of experience with big data and cloud architecture
• 3+ years of hands‑on experience building modern data pipelines within a major cloud platform (preferably GCP, open to AWS or Azure)
• 3+ years of experience with deployment/scaling of apps on containerized environments (i.e., Kubernetes, AKS)
• 3+ years of experience with real‑time and streaming technology (i.e., Azure Event Hubs, Azure Functions, Kafka, Spark Streaming)
• 1+ year of soliciting complex requirements and managing relationships with key stakeholders
• 1+ year of experience independently managing deliverables

• Experience building Agentic AI tools
• Experience with Git, CI/CD pipeline, and other Dev Ops principles/best practices
• Experience with bash shell scripts, UNIX utilities, and 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 complex systems and solving challenging analytical problems
• Strong collaboration and communication skills within and across teams
• Google Professional Data Engineer Certification
• Knowledge of microservices and SOA
• Formal SAFe and/or agile experience
• Previous healthcare experience and domain knowledge

• Bachelor’s Degree or equivalent work experience in Computer Science, Information Systems, Data Engineering, Data Analytics, Machine Learning, or related field required
• Master’s Degree preferred

Anticipated Weekly

Hours:

4…