At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care. As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day. We are seeking a seasoned data engineering professional to lead our data modeling and data product delivery. Candidates will possess a deep understanding of data architecture and data modeling. They will be responsible for managing a team of data engineers, ensuring timely delivery of projects and providing technical leadership and guidance. This role involves collaborating with other engineering teams and product owners, taking ownership of the team's work, and influencing the technical strategy and architecture of the platform. The position is a blend of leadership and hands-on technical guidance and requires an understanding of data engineering best practices and the ability to translate business requirements into technical solutions. You will lead a dedicated team creating datasets for analytic and data science workloads. Data Pipeline Development: Ovre see the design and buildout of ETL/ELT data pipelines to ingest, process, and transform large datasets from multiple sources. Performance Optimization: Implement best practices for performance tuning, partitioning, and clustering to optimize data queries and reduce costs. Data Quality & Governance: Establish and enforce data quality standards, data governance frameworks, and security policies for data storage and access. Documentation & Knowledge Sharing: Create comprehensive documentation for data pipelines, workflows, and processes. Share best practices and mentor junior data engineers. Design and architect data infrastructure analytical workloads.