Senior Software Engineer, Payer Ops & AI Automation

CVS Health; Wilmington (VT); On-site; USD 83,000 - 222,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Paid time off

Retirement savings options

Job summary

CVS Health is seeking a skilled Data Engineer to design, develop, and implement digital solutions that optimize the Payer Operations ecosystem. You will architect integration patterns between cloud-native SaaS, Epic EMR, and the Enterprise Data Platform, and collaborate with cross-functional teams to modernize payer metadata and lifecycle processes.

The role emphasizes AI-driven innovation, robust testing, and scalable design, with a strong focus on data quality, governance, and performance

Qualifications

• 5+ years of experience with SQL and relational DBMS
• Hands-on experience with dimensional data modeling and data warehousing
• Programming in SQL, Python, and related languages for cloud/on‑prem data warehousing services
• Troubleshooting data issues and applying performance improvements
• Strong written and verbal communication skills

Responsibilities

• Design end-to-end integration patterns across cloud-native SaaS and core clinical systems
• Conduct system testing, debugging, and code reviews to ensure reliability
• Serve as technical consultant to Product and Business leads for design decisions
• Explore AI/ML to drive intelligent automation in development
• Create and maintain architecture diagrams and governance documentation

Skills

SQL

Dimensional data modeling

Python

Data warehousing

Debugging

Communication skills

Education

Bachelor's degree in Computer Science or related field

Job description

CVS Health is seeking a skilled Data Engineer to design, develop, and implement digital solutions that optimize the Payer Operations ecosystem. You will architect integration patterns between cloud-native SaaS, Epic EMR, and the Enterprise Data Platform, and collaborate with cross-functional teams to modernize payer metadata and lifecycle processes.

The role emphasizes AI-driven innovation, robust testing, and scalable design, with a strong focus on data quality, governance, and performance