Senior Data Platform Engineering Manager

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.

Position Summary

We are seeking an experienced Senior Data Platform Engineering Manager to lead and grow our newly established Azure Databricks data platform. This role is central to our data strategy, requiring a leader who can manage technical teams, define our platform's future, and ensure it meets the evolving needs of our engineers and business. The ideal candidate will have deep expertise in cloud data technologies and a proven track record of managing and scaling data platforms.

We also have current data Platforms on-prem (MS SQL server) and Cloud (Palantir Foundry) that this role will support those platforms as well until we have migrated off those platforms and completely on Azure Databricks. 

This role sits at the intersection of platform engineering, cloud engineering, data governance, and developer enablement, requiring a blend of deep technical expertise, strategic thinking, and a passion for building scalable, reliable, and secure systems. 
 

Responsibilities:

• Platform Strategy & Leadership:

  • Own the strategic vision and roadmap for the Azure Databricks platform, aligning it with company-wide data and business goals.

  • Lead, mentor, and build a high-performing team of data engineers and platform specialists.

  • Act as the primary point of contact for platform-related issues and opportunities, communicating effectively with executive leadership and technical teams.

• Platform Oversight & Maintenance:

  • Ensure new data engineering team members are onboarded consistently with best practices

  • Advocate for best practices, create reusable patterns and libraries, and provide expert-level technical support and training to data engineering teams.

  • Ensure the platform's operational health, including performance, security, and cost management.

  • Oversee platform maintenance, upgrades, and migrations to ensure reliability and minimize downtime.

  • Establish and enforce best practices for development, data governance, quality, and security on the platform.

• Enhancement & Innovation:

  • Drive the continuous enhancement of the platform by introducing new tools, features, and capabilities.

  • Evaluate and integrate new data technologies to improve efficiency, scalability, and performance.

• Cross team collaboration

  • Act as the central liaison for cross-functional teams like DBA, Data Engineering, Cloud Engineering, and TechOps to ensure seamless alignment and implementation of changes across both on-premise and cloud platforms

  • Establish a shared vision for the Data Platforms by working with engineering and product leaders from other teams to define a clear, shared vision for the platform. This ensures all teams are pulling in the same direction and understand how their work contributes to the larger company goals.

Required Skills & Qualifications

• Experience: 8+ years of experience in data engineering, platform management, or a related role, with a strong focus on cloud data technologies.Proven experience managing and leading technical teams.

• Azure Databricks Expertise: Deep, hands-on experience with the Azure Databricks platform, including its administration, cluster management, job orchestration, and key features like Delta Lake and Unity Catalog. Relevant certifications such as Microsoft Certified: Azure Solutions Architect Expert,  Databricks Certified Data Engineer Professional, and Databricks Certified Platform Administrator

• Distributed Systems: A strong understanding of distributed computing principles and the architecture of large-scale data systems.

• Problem-Solving: Exceptional analytical and problem-solving skills with a track record of diagnosing and resolving complex, platform-level issues.

• Communication: Excellent communication, documentation, and presenta