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.
Position Summary
This is a hybrid position - in a hub office 1 to 3 days a week. Must be local to Wellesley MA, Hartford CT, New York City, or Irving TX.
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. Collaborating closely with teams, you will craft tools to provide actionable insights and integrate them with consumer touchpoints.
In this role, you will:
Architect and develop robust, scalable ETL/ELT pipelines using Cloud Dataflow, Cloud composer (Airflow), and Pub/Sub for both batch and streaming use cases. Leverage BigQuery as the central data warehouse and design integrations with other GCP services (e.g., Cloud storage, Cloud functions).
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.
Lead architectural decisions for data platforms and mentor junior engineers on cloud-native data engineering patterns. Promote best practices for code quality, version control, cost optimization, and data security in a GCP environment. Drive initiatives around data democratization, including building reusable datasets and data catalogs via Dataplex or Data Catalog.
Design, develop, and maintain enterprise AI/ML solutions and platforms that address complex business and customer challenges. Integrate Large Language Models (LLMs), generative AI capabilities, and AI agents into products and data ecosystems. Define the technical architecture and infrastructure required for AI applications, and build scalable platforms supporting model training, deployment, monitoring, governance, and lifecycle management while ensuring security, reliability, and operational excellence.
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, that will allow you to grow your technical skills and engineering expertise.
Required Qualifications
3-5+ years of experience with SQL, NoSQL
3-5+ years of experience with Python (or a comparable scripting language)
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 and managing cloud infrastructure on Google Cloud Platform (GCP), including Cloud Storage, BigQuery, Dataflow, and Dataproc
3+ years of experience deploying and scaling containerized applications on GCP using Google Kubernetes Engine (GKE), Cloud Run, and Artifact Registry
3+ years of experience with real-time and streaming data technologies on GCP (i.e. Pub/Sub, Dataflow, Cloud Functions, Apache Kafka, Spark Streaming)
1+ year(s) of soliciting complex requirements and managing relationships with key stakeholders
1+ year(s) of experience independently managing deliverables
Preferred Qualifications
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
Ability to leverage multiple tools and programming languages to analyze and manipulate data sets from disparate data sources
Knowledge of API development
Exposure to Generative AI
Exposure Large Language Models (GPT, Claude, Gemini, Llama, etc.)
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 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
Education
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
40Time Type
Full timePay Range
The typical pay range for this role is:
$92,700.00 - $222,480.00This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.
Additional details about available benefits are provided during the application process and on Benefits Moments.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
Skills Required
- 3-5+ years of experience with SQL and NoSQL
- 3-5+ years of experience with Python or a comparable scripting language
- 3+ years of experience with data warehouses, data modeling, technical architectures, and infrastructure components
- 3+ years of experience with ETL/ELT and building high-volume data pipelines
- 3+ years of experience with reporting and analytical tools
- 3+ years of experience with query optimization, data structures, transformation, metadata, dependencies, and workload management
- 3+ years of experience with big data and cloud architecture
- 3+ years of hands-on experience managing cloud infrastructure on GCP, including Cloud Storage, BigQuery, Dataflow, and Dataproc
- 3+ years of experience deploying and scaling containerized applications on GCP using GKE, Cloud Run, and Artifact Registry
- 3+ years of experience with real-time and streaming data technologies, including Pub/Sub, Dataflow, Cloud Functions, Apache Kafka, or Spark Streaming
- 1+ year of experience soliciting complex requirements and managing relationships with key stakeholders
- 1+ year of experience independently managing deliverables
- Bachelor's degree or equivalent work experience in Computer Science, Information Systems, Data Engineering, Data Analytics, Machine Learning, or a related field
- Experience designing and building data engineering solutions in cloud environments, preferably GCP
- Experience with Git, CI/CD pipelines, and DevOps best practices
- Experience with Bash shell scripts, UNIX utilities, and UNIX commands
- Ability to use multiple tools and programming languages to analyze and manipulate data from disparate sources
- Knowledge of API development
- Exposure to generative AI
- Exposure to large language models such as GPT, Claude, Gemini, or Llama
- Experience solving complex analytical problems and working with complex systems
- Strong collaboration and communication skills
- Knowledge of data visualization and reporting
- 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 warehouses and data lakes
- Master's degree
CVS Health Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about CVS Health and has not been reviewed or approved by CVS Health.
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Healthcare Strength — Health coverage includes medical, dental, and vision with HSA-eligible options, free preventive care, virtual care, and access to MinuteClinic services. Mental-health resources such as counseling support are emphasized, and coverage is often considered solid for full-time colleagues.
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Retirement Support — A dollar-for-dollar 401(k) match up to 5% after one year and an Employee Stock Purchase Plan are consistently highlighted in Total Rewards materials. Feedback suggests retirement programs are a meaningful strength within the overall package.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings include up to 20 no-cost counseling sessions per issue, backup care, tuition assistance, and substantial in-store discounts, alongside broader wellness tools. These everyday perks expand value beyond base pay and can be especially meaningful for full-time schedules.
CVS Health Insights
What We Do
CVS Health is the leading health solutions company that delivers care in ways no one else can. We reach people in more ways and improve the health of communities across America through our local presence, digital channels and our nearly 300,000 dedicated colleagues – including more than 40,000 physicians, pharmacists, nurses and nurse practitioners. Wherever and whenever people need us, we help them with their health – whether that’s managing chronic diseases, staying compliant with their medications, or accessing affordable health and wellness services in the most convenient ways. We help people navigate the health care system – and their personal health care – by improving access, lowering costs and being a trusted partner for every meaningful moment of health. And we do it all with heart, each and every day.
