Senior Manager, Data Engineering & AI

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.

A Brief Overview

Leads and actively contributes to a team that builds the systems and AI-enabled platforms used to process, store, and serve data across the enterprise. This is a player coach role: roughly 50% of the time is spent hands-on in design, code, and architecture, with the remainder devoted to people leadership, cross-functional partnership, and strategy. The Senior Manager owns the growth, performance, and delivery of the team, partners closely with product, data science, and business teams, and turns emerging ideas into production-grade solutions.

Position Summary

The Senior Manager, Data Engineering & AI is both a people leader and a technical leader who leads from the front. This person manages a team of data and software engineers (employees and contractors), owns their development, performance, and delivery, and stays close to the work by committing approximately 50% of their time to hands on engineering, including prototyping, building core components, setting patterns, and solving the hardest technical problems alongside the team.

The role sits at the intersection of engineering, product, data science, and the business. The Senior Manager works with product managers to shape roadmaps, with data scientists to move models from experiment to production, and with business stakeholders to ensure data and AI investments deliver measurable outcomes. The ideal candidate combines deep full stack and data engineering expertise, strong software engineering fundamentals, and first principles thinking with a genuine commitment to building people and relationships. Experience in healthcare and contact center analytics engineering is highly valued.

What You Will Do

People Management & Team Leadership

• Manages a team of software engineers and data engineers, including hiring, onboarding, goal setting, performance management, career development, and retention.
• Provides regular coaching, feedback, and recognition, and addresses performance concerns directly and constructively.
• Mentors engineers, identifies skill gaps, and provides training and growth opportunities to strengthen team capabilities.
• Leads a blended team of employees and contractors, ensuring clear expectations, accountability, and a cohesive team culture.
• Plans team capacity and priorities, balancing delivery commitments, technical debt, and individual growth.
• Models a growth mindset, encouraging experimentation, learning, and continuous improvement.

Hands-On Engineering & Technical Leadership

• Dedicates approximately 50% of time to hands-on work, including designing, coding, prototyping, and troubleshooting data pipelines, services, and AI enabled applications.
• Sets the bar for engineering quality by authoring reference implementations, establishing patterns, and tackling the most complex technical challenges alongside the team.
• Performs code reviews and enforces coding standards, based on company and industry requirements, across the development teams.
• Applies first principles thinking and sound design fundamentals to simplify complex problems and avoid unnecessary complexity.

Strategy & Architecture

• Defines strategy for the full software development lifecycle, utilizing emerging technologies and key data design principles in developing data pipelines, interfaces, and architecture to support data and analytics initiatives.
• Develops and executes a strategic roadmap for data driven and AI enabled software projects, aligning them with business objectives and the overall technology vision.
• Decides on the adoption of industry standard data and advanced analytics capabilities by leveraging existing services and identifying industry leading solutions.
• Identifies and mitigates technical risks, proactively addressing issues that may affect project success, data quality, or data integrity.

AI & Data Engineering

• Leads the design and delivery of AI and ML-enabled data products, including GenAI, RAG, and LLM-based solutions, along with supporting data foundations, MLOps/LLMOps practices, and evaluation frameworks.
• Builds scalable, reliable, and cost-efficient pipelines and platforms for batch and real-time data processing.

Cross-Functional Partnership

• Product: Partners with product managers and UX/UI designers to define requirements, shape roadmaps, prioritize work, and translate needs into technical specifications and deliverables.

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