Lead Director, Software Development Engineering

Position Summary

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.

Our Analytics Engineering team within the Data & Analytics division of our Data, Digital, Analytics, Technology (DDAT) organization is seeking a Lead Director, Software Development Engineering. We are looking for passionate, driven individuals who are ready to lead a team of analytics engineers (software, ML, data) who support Aetna’s data science teams. Our work ensures that we apply the tools and resources at our disposal to deliver a best-in-class experience for our members, providers and plan sponsors.

This leadership role has a broad technical portfolio of data, analytics, software and machine learning assets that ensure our teams are able to build and deploy intelligence at scale across batch and real-time use cases. As the healthcare landscape evolves and changes, our team’s work is a crucial part of the overall CVS Health mission: transforming care to drive superior health outcomes and a seamless patient and consumer experience.

• Technical oversight:
  Design and oversee the build‑out and operations of complex distributed systems at scale in a fast‑paced analytics organization.
• Engineering leadership:
  Technically direct, support, and evaluate data, software, and ML engineers and their work product, ensuring best‑in‑class solutions that can scale to meet future non‑functional requirements.
• System performance:
  Monitor and optimize both team and system performance, identifying opportunities for enhancement and addressing any issues or bottlenecks. Establish KPIs and OKRs that unlock quantitative insight.
• Talent management:
  Recruit, manage, mentor, and retain a high‑performing engineering team while fostering a positive and supportive culture, encouraging innovation and continuous improvement.
• End‑to‑end ownership:
  Lead teams from strategy through delivery in complex and highly visible engineering projects.
• Prioritization and pivots:
  Guide the team’s work prioritization in alignment with strategic objectives, coaching implementation teams through pivots while staying focused on the overall objective.
• Cross‑functional collaboration:
  Collaborate closely with engineering, platform, infrastructure, security, governance and other technical teams to develop solutions that meet appropriate guidelines.
• Coalition building:
  Establish effective relationships with partners and customers, understanding their vision and helping deliver on their goals.
• Risk management:
  
  Proactively identify, communicate, and mitigate internal and external risks; communicate progress and challenges to senior management and stakeholders.
• The big picture:
  Understand how data, data science, and AI/ML can drive clinical and healthcare delivery strategies; build partnerships that enable business innovation through data and analytics.
• Staying current:
  Stay updated on industry trends, emerging technologies, and best practices in software development, analytics, data engineering, and machine learning to drive innovation and efficiency.

• 10+ years as a hands‑on software development engineer.
• 5+ years designing and building high‑volume distributed software systems.
• 5+ years recruiting, managing, and retaining a high‑performing team of software development professionals in an agile environment.
• 2+ years developing containerized software applications in public cloud.
• 2+ years exposure to analytics, data engineering and machine learning lifecycle, tools, and best practices.
• 2+ years designing, building, and operating real‑time streaming systems and associated system‑building blocks (messaging, caching, etc.).
• 1+ year managing engineering managers.
• 1+ year using generative AI as an integrated component in software solutions.
• 1+ year in the healthcare or health…