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Added 12 mins ago
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CVS Health

Senior Manager, Data Engineering & AI

Wellesley, MA, United States

$118,450.00 - $284,280.00

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Job details

Pay: $118,450.00 - $284,280.00
Posting language: English
Posted: Nov 3, 2026

Original job description

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.
Data Science: Partners with data scientists and analytics teams to productionize models and prototypes into secure, observable, scalable systems, and ensures the data foundations needed for experimentation and model performance are in place.
Business: Builds and sustains strong relationships with business stakeholders to understand priorities, shape the direction of data and AI investments, and demonstrate measurable value.
Communicates complex technical and analytical results to technical and non-technical leaders in a clear and concise manner.

Ideation & Innovation

Generates and champions new ideas, running proofs of concept and experiments to validate value quickly and scale what works.
Stays current on emerging AI and data engineering technologies and brings pragmatic recommendations to the team and leadership.

Required Qualifications

8+ years of experience in data engineering, software engineering, or a related field.
3+ years of people management experience, including hiring, performance management, and developing engineers.
Demonstrated ability and willingness to commit approximately 50% of time to hands-on design and development.
Deep understanding of full stack engineering, software engineering principles, design fundamentals, and first-principles problem solving.
Strong proficiency in Python and SQL, plus at least one additional language (e.g., Java, Scala, or JavaScript/TypeScript).
Proven experience designing and building data pipelines, data models, and data platforms on a major cloud provider (GCP, AWS, or Azure).
Hands-on experience applying AI/ML or GenAI in production data environments.
Experience working closely with product, data science, and business teams to deliver outcomes.
Strong knowledge of CI/CD, testing, observability, and DevOps practices for data and software systems.
Adept at execution and delivery (planning, delivering, and supporting).
Adept at business intelligence and translating business needs into technical solutions.
Adept at collaboration, teamwork, and building relationships across organizational boundaries.
Mastery of problem solving and decision making.
Mastery of growth mindset (agility and developing yourself and others).
Excellent written and verbal communication skills, with the ability to influence senior stakeholders.

Preferred Qualifications

Experience in healthcare data environments, including familiarity with HIPAA, PHI handling, and healthcare data standards.
Experience with contact center analytics engineering, such as call transcription, speech and text analytics, call driver/reason classification, and customer experience metrics.
Hands-on experience with LLM application frameworks (e.g., LangChain, LangGraph), vector databases, and managed AI platforms (e.g., Vertex AI).
Experience with data governance, data quality, lineage, and access control practices.
Experience managing blended teams of employees and contractors, including managers or team leads.
Familiarity with engineering performance measurement frameworks such as DORA.
Track record of driving innovation, from idea through proof of concept to production adoption.

Education

Master’s degree in Computer Science, Engineering, or a related field.

Pay Range

The typical pay range for this role is:

$118,450.00 - $284,280.00

This 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. This position also includes an award target in the company’s equity award program.

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.

This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.

Additional details about available benefits are provided during the application process and on Benefits Moments (https://learn.bswift.com/cvshealth-mainland) .

We anticipate the application window for this opening will close on: 02/05/2027

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

CVS Health is an equal opportunity/affirmative action employer, including Disability/Protected Veteran - committed to diversity in the workplace.

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More about this job

Skills

Data engineering
Team leadership
Onboarding
Performance management
Coaching
Process improvement
Leadership
Software development
Design principles
ML
Process data
Engineering principles
Problem solving
Python
SQL
Oracle Java
Scala
JavaScript
TypeScript
Data models
Google Cloud
AWS
Microsoft Azure
CI/CD
DevOps
Business intelligence
Collaboration
Teamwork
Relationship building
Decision making
Communication skills
Customer experience
LangChain
Computer science

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