Sr Mgr, Software Engineering - Provider Network Performance

at  CVS Health

Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver.
Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.

POSITION SUMMARY

Our Network Performance Analytics Engineering team within the Analytics & Behavior Change (A&BC) division of our Data, Digital, Analytics, Technology (DDAT) organization is seeking a Senior Manager, 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 Network Performance data science team. Our work puts actionable insights into the hands of the Aetna team members who are working to establish Aetna’s position in new markets and negotiate provider contracts.
This leadership role has a broad technical portfolio of data, analytics, software and machine learning assets that ensure our network teams are armed with the competitive intelligence they need to ensure the health of Aetna’s network and contracts. 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 Senior Manager, you will be responsible for guiding a team 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.

REQUIRED QUALIFICATIONS

• 6+ years as a hands-on software development engineer
• 4+ years designing & building high-volume distributed software systems
• 3+ 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.)
• 2+ years managing engineers
• 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

EDUCATION

Bachelor’s degree in a software discipline, or equivalent work experience.
Master’s degree preferred.

• 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 a team 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 an implementation team 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.