Position Summary 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.
As a Lead Director, you will be responsible for guiding teams as they build best-in-class applications that integrate advanced analytics capabilities (predictive models, LLMs, vector search) into applications and data products built within the Google Cloud Platform. You will develop the strategies and tactics that we use on the path to delivering cutting-edge products, leveraging your expertise in engineering management, software architecture, and agile development lifecycles. As you join a high-caliber group of engineering leaders dedicated to delivering impact quickly while ensuring our technical assets and architecture are constantly maturing, your experience, instincts, and insights will enable us to iterate quickly while we explore bold technical solutions to complex problems. You encourage the team and champion the delivery of the right software at the right time, ensuring that we maximize our impact.
Responsibilities:- Technical oversight: Technical leader capable of designing and overseeing the build-out and operations of complex distributed systems at scale in a fast-paced analytics organization
- Engineering leadership: Able to technically direct, support, and evaluate data, software, and ML engineers and their work product, ensuring we are building best-in-class solutions that can scale to meet our future non-functional requirements
- System performance: Monitor and optimize both team & system performance, identifying opportunities for enhancement and addressing any issues or bottlenecks. Establish KPIs and OKRs that unlock quantitative insight so we can change processes with confidence.
- Talent management: Recruit, manage, mentor, and retain a high-performing engineering team while contributing to a positive and supportive culture, encouraging innovation, and driving a pragmatic balance of continuous improvement and effective value delivery.
- End-to-end ownership: Lead teams from strategy through delivery in complex and highly visible engineering projects.
- Prioritization and pivots: Guides team's work prioritization in alignment with our strategic objectives. Coach implementation teams through pivoting as needed while remaining steadfastly focused on the overall objective.
- Cross-functional collaboration: Collaborate closely with other technical teams (engineering, platform, infrastructure, security, governance) to understand their expectations and develop solutions in accordance with appropriate guidelines.
- Coalition building: Establish effective relationships with partners and customers, ensuring that you understand their vision and can help them deliver on their goals.
- Risk management: Proactively identify, communicate, and mitigate both internal and external risks. Communicate clearly on progress, challenges, and opportunities to senior management and stakeholders, including presenting technical concepts to non-technical audiences.
- 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 technologies to drive innovation and efficiency.
Required Qualifications- 10+ years as a hands-on software development engineer
- 5+ years designing & 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 insurance industry with deep understanding of health care value chain
Preferred Qualifications - Strong experience in web services, microservice and service-oriented architectures
- Expert in Python, Java, Go, .NET or other similar programming languages
- Expert in SQL, relationship database management systems, and non-relational or no-SQL database management systems.
- Ability to diagram complex software architectures and communicate complex engineering ideas to non-technical stakeholders both visually and verbally
- Expert in relationship management for both technical and non-technical customers and stakeholders
- Strong understanding of cloud-based technologies (GCP, Azure, AWS), engineering frameworks and tools
- Experience delivering in Agile, SAFE, Kanban, and Lean practices.
- Experience in data strategy, data architecture, cloud software engineering design patterns, data science & machine learning methodologies, systems integrations, analytics/BI program management (SQL, Python, R, Java)
- Understanding and familiarity with CI/CD, cloud devops, containers (kubernetes/Docker, etc.), Python/PySpark, dataproc, dataflow, pub/sub, and other GCP managed services
EducationBachelor's degree in a software discipline, or equivalent work experience.
Master's degree preferred.
Pay RangeThe typical pay range for this role is:
$144,200.00 - $288,400.00
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.
Great benefits for great peopleWe 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: 06/29/2026
