Hiring.Camp

Executive Director, Data Engineering - Retail Analytics

CVS Health

·

Aug 18, 2026

Salary
$175k – $335k
Location
Woonsocket-1 CVS Drive, United States of America · Work At Home-Connecticut · Work At Home-New York · Work At Home-Texas · Work At Home-Massachusetts
Workplace
Remote
Type
Full-time
Department
Engineering
Seniority
Director
Experience
7+ years
Education
Master
Closing date
Today
Source
Workday

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.

Position Summary

The Executive Director, Data Engineering serves as a senior technology leader within Analytics Engineering, responsible for defining and executing the data engineering strategy that powers CVS Health's Retail analytics ecosystem.

This role leads a large, multi-disciplinary engineering organization focused on designing, building, and scaling enterprise data platforms, AI products, and engineering capabilities that support Retail Pharmacy, Front Store, Retail Supply Chain, Merchandising, Personalization, Pricing, Marketing, and Operational analytics initiatives.

This leader partners closely with Data Science, Product, Analytics, Architecture, and business stakeholders to deliver reliable, scalable, cloud-based data solutions that accelerate insight generation and enable advanced analytics and AI-driven decision-making.

The Executive Director drives engineering excellence, talent development, platform modernization, and operational rigor while ensuring alignment with enterprise technology strategy and business priorities.

Required Qualifications:

  • 15+ years of progressive experience in Data Engineering, Software Engineering, Analytics Engineering, or related technology disciplines.
  • 7+ years of experience leading large engineering organizations through multiple layers of leadership.
  • Proven experience designing and delivering enterprise-scale data platforms, data products, and cloud-native engineering solutions.
  • Deep expertise in modern data engineering practices, including data pipelines, distributed processing, cloud platforms, data governance, and platform reliability.
  • Demonstrated success partnering with Analytics, Data Science, Product, and business organizations to translate complex business needs into scalable technology solutions.
  • Strong experience leading large transformation initiatives, platform modernization efforts, and organizational change.
  • Adept at execution and delivery, including strategic planning, roadmap development, and operational management.
  • Adept at business intelligence and data-driven decision making.
  • Mastery of collaboration, stakeholder management, and executive communication.
  • Mastery of problem solving, strategic thinking, and organizational leadership.
  • Mastery of growth mindset principles with a demonstrated ability to develop leaders and build high-performing teams.

Preferred Qualifications:

  • Experience supporting Retail, Pharmacy, Merchandising, Supply Chain, Marketing, Consumer, or Omnichannel analytics environments.
  • Experience building and scaling enterprise data products, feature stores, real-time data solutions, or analytics enablement platforms.
  • Strong knowledge of cloud-based data ecosystems, platform engineering, DevOps, DataOps, and engineering best practices.
  • Experience enabling AI, machine learning, and advanced analytics solutions through robust data engineering capabilities.
  • Experience operating within a highly regulated, large-scale enterprise environment.
  • Demonstrated ability to influence senior executives and drive alignment across complex organizational structures.
  • Track record of building engineering cultures centered on innovation, accountability, continuous improvement, and delivery excellence.

Education:

Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics, Statistics, or a related quantitative field required.

Master's degree in Computer Science, Engineering, Business Administration, Data Science, or a related discipline preferred.

Pay Range

The typical pay range for this role is:

$175,100.00 - $334,750.00


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.

We anticipate the application window for this opening will close on: 09/18/2026

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

Skills

Machine LearningData ScienceData EngineeringDevOpsMerchandisingStrategic Planning

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