Senior Manager, Data Engineering & AI

CVS Health•Irving, TX

2d•$118,450 - $284,280

About The Position

The Senior Manager, Data Engineering & AI is a people and technical leader responsible for a team of software and data engineers, including employees and contractors. This player-coach role spends approximately 50% of its time on hands-on engineering work, such as design, coding, prototyping, architecture, and solving complex technical challenges, while also overseeing team development, performance, and delivery. The role works across engineering, product, data science, and business teams to shape roadmaps, productionize models, and ensure data and AI investments deliver measurable outcomes. The Senior Manager defines strategy and architecture for data pipelines, interfaces, platforms, and AI-enabled software; leads the development of AI/ML-enabled data products, including GenAI, RAG, and LLM-based solutions; and establishes supporting data foundations, MLOps/LLMOps practices, and evaluation frameworks. The position also promotes engineering quality, manages technical risks, and champions experimentation and continuous improvement. Healthcare and contact center analytics engineering experience is highly valued.

Requirements

At least 8 years of experience in data engineering, software engineering, or a related field.
At least 3 years of people management experience, including hiring, performance management, and developing engineers.
Ability and willingness to spend approximately 50% of the time on 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 such as 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.
Ability to plan, deliver, and support work effectively.
Ability to apply business intelligence and translate business needs into technical solutions.
Ability to collaborate, work in teams, and build relationships across organizational boundaries.
Mastery of problem solving and decision making.
Mastery of growth mindset, including agility and developing oneself and others.
Excellent written and verbal communication skills, including the ability to influence senior stakeholders.

Nice To Haves

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 or reason classification, and customer experience metrics.
Hands-on experience with LLM application frameworks such as LangChain or LangGraph, vector databases, and managed AI platforms such as 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.

Responsibilities

Manage a team of software and data engineers, including hiring, onboarding, goal setting, performance management, career development, and retention.
Coach and mentor engineers, provide feedback and recognition, address performance concerns, identify skill gaps, and provide training and growth opportunities.
Lead a blended team of employees and contractors by setting expectations, fostering accountability, and building a cohesive team culture.
Plan team capacity and priorities, balancing delivery commitments, technical debt, and individual growth.
Spend approximately 50% of the role on hands-on engineering, including designing, coding, prototyping, and troubleshooting data pipelines, services, and AI-enabled applications.
Establish engineering quality through reference implementations, patterns, code reviews, coding standards, and direct involvement in complex technical challenges.
Apply sound design fundamentals and first-principles thinking to simplify complex problems and avoid unnecessary complexity.
Define strategy for the software development lifecycle and develop and execute roadmaps for data-driven and AI-enabled software projects aligned with business objectives and technology vision.
Evaluate industry-standard data and advanced analytics capabilities, leveraging existing services and identifying leading solutions.
Identify and mitigate technical risks that could affect project success, data quality, or data integrity.
Lead the design and delivery of AI/ML-enabled data products, including GenAI, RAG, and LLM-based solutions, and supporting data foundations, MLOps/LLMOps practices, and evaluation frameworks.
Build scalable, reliable, and cost-efficient platforms and pipelines for batch and real-time data processing.
Partner with product managers and UX/UI designers to define requirements, shape roadmaps, prioritize work, and translate needs into technical specifications and deliverables.
Partner with data scientists and analytics teams to productionize models and prototypes into secure, observable, scalable systems and provide the data foundations needed for experimentation and model performance.
Build relationships with business stakeholders, understand priorities, shape data and AI investments, and demonstrate measurable value.
Communicate complex technical and analytical results clearly to technical and non-technical leaders.
Generate and champion ideas, run proofs of concept and experiments, and scale approaches that demonstrate value.
Stay current on emerging AI and data engineering technologies and make pragmatic recommendations to the team and leadership.