Lead Java Engineer, HealthTech Platform

CVS Health

Tennessee

Hybrid

USD 107,000 - 261,000

Full time

4 days ago
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Job summary

CVS Health is seeking a hands-on Lead Java Software Development Engineer to join a fast-paced team transforming the digital experience of pharmacy and health care. You will collaborate with architects and developers, drive end-to-end development and delivery, and ensure scalable, secure cloud-based solutions.

With a focus on healthcare interoperability and cloud-native applications, you will mentor engineers, participate in Agile processes, and help optimize performance across front- and

Qualifications

  • 10+ years in software development lifecycle including ideation, coding, testing, and deployments.
  • 7+ years with Java, Spring, Junit, APIs using Spring Boot and microservices.
  • 3+ years supporting healthcare clinical applications.
  • 3+ years deploying and managing cloud apps (prefer Google Cloud).

Responsibilities

  • Lead and mentor engineers onsite and offshore to deliver use cases.
  • Collaborate with cross-functional teams to optimize performance and code quality.
  • Own end-to-end development, deployment, and observability of services.
  • Participate in PI planning and Agile Scrum ceremonies.

Skills

Team leadership
Agile practices
Communication
Problem solving

Education

Bachelor's degree or equivalent

Tools

Java
Spring
Junit
Mockito
Spring Boot
Microservices
Kubernetes
IntelliJ
Git
Jenkins
Github Actions
GCP
Azure
AWS
Apigee
Dataflow
Prometheus
Grafana
OAuth2.0
JWT
SQL
NoSQL
Postgres
MongoDB

Job description

CVS Health is seeking a hands-on Lead Java Software Development Engineer to join a fast-paced team transforming the digital experience of pharmacy and health care. You will collaborate with architects and developers, drive end-to-end development and delivery, and ensure scalable, secure cloud-based solutions.

With a focus on healthcare interoperability and cloud-native applications, you will mentor engineers, participate in Agile processes, and help optimize performance across front- and

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