Senior Data Engineer, CVS Health

CVS Health

Location:
United States, Wellesley

Category:
IT - Software Development

Contract Type:
Employment contract

Salary:

101970.00 - 222480.00 USD / Year

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Job Description:

As a Senior Data Engineer at CVS Health, 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. 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 lead architectural decisions for data platforms and collaborate closely with teams, crafting tools to provide actionable insights and integrate them with consumer touchpoints.

Job Responsibility:

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 Datapelx or Data Catalog

Requirements:

3+ years of experience with SQL, NoSQL
3+ 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 modern data pipelines within a major cloud platform (GCP, AWS, Azure)
3+ years of experience with deployment/scaling of apps on containerized environment (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(s) of soliciting complex requirements and managing relationships with key stakeholders
1+ year(s) of experience independently managing deliverables

Nice to have:

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
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

What we offer:

Affordable medical plan options, a 401(k) plan (including matching company contributions), and an employee stock purchase plan
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching
Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility

Additional Information:

Job Posted:
June 15, 2025

Expiration:
July 31, 2025

Employment Type:

Fulltime

Work Type:

Hybrid work

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Senior Data Engineer