Healthcare Data & AI Integration Engineer

CVS Health; Central City (NE); On-site; USD 83,000 - 222,000; Full time

Benefits offered by this job

Health insurance

Dental & vision coverage

Paid time off

Retirement plan

Job summary

CVS Health is seeking a senior data engineering professional to design, develop, and implement digital solutions for Payer Operations. You will architect data integration patterns across cloud-native and on-prem systems, optimize metadata, and automate payer lifecycle contracts.

This role emphasizes building scalable data pipelines, performing system testing, and collaborating with cross-functional teams while leveraging AI/ML to improve automation and insights.

Qualifications

• Bachelor's degree in CS/IT or related field; equivalent work experience acceptable.
• 5+ years of hands-on SQL and relational DB experience required.
• Experience with dimensional data modeling and data warehousing preferred.

Responsibilities

• Architect and build end-to-end integrations bridging cloud-native SaaS and core clinical systems.
• Ensure quality through testing, debugging, and peer code reviews for scalable solutions.
• Act as technical consultant to product and business leads and refine requirements.
• Explore AI/ML options to drive automation and smarter development processes.
• Document designs, diagrams, and governance to enable platform self-service.
• Navigate ambiguity and collaborate with stakeholders to deliver solutions.

Skills

SQL & RDBMS

Dimensional modeling

Data warehousing

Python

Data troubleshooting

Performance tuning

Ownership & teamwork

Communication skills

Education

Bachelor's degree in Computer Science / IT

Tools

HL7

FHIR

Epic EMR

Job description

CVS Health is seeking a senior data engineering professional to design, develop, and implement digital solutions for Payer Operations. You will architect data integration patterns across cloud-native and on-prem systems, optimize metadata, and automate payer lifecycle contracts.

This role emphasizes building scalable data pipelines, performing system testing, and collaborating with cross-functional teams while leveraging AI/ML to improve automation and insights.