6 часов назад
DevOps Engineer (AWS/Kubernetes)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
DevOps Engineer (AWS/Kubernetes): Building and maintaining secure, scalable, HIPAA- and HITRUST-compliant cloud infrastructure with an accent on AWS and Azure, CI/CD, infrastructure as code, and container orchestration. Focus on developing Python-based deployment automation, implementing observability with Prometheus, Grafana, and Splunk, and ensuring high availability across complex cloud environments.
Location: United States
Company
develops a healthcare data platform that helps health plans create trusted, connected data foundations for better care and cost decisions.
What you will do
- Build and maintain secure, scalable, HIPAA- and HITRUST-compliant infrastructure across AWS and Azure.
- Design highly available cloud infrastructure and contribute to DevOps architecture, CI/CD, and infrastructure-as-code practices.
- Develop Python-based CI/CD automation for testing, validation, and deployment workflows.
- Build and manage Docker and Kubernetes environments, including EKS, AKS, and self-hosted clusters.
- Implement monitoring and observability with Prometheus, Grafana, and Splunk.
- Collaborate with engineering, product, and security teams to improve deployment practices and remove technical obstacles.
Requirements
- 4+ years of development experience, including work with complex systems.
- Strong cloud experience, preferably with AWS.
- Solid knowledge of Linux systems administration and networking.
- Experience implementing CI/CD with GitLab, Jenkins, Travis, or a comparable platform.
- Knowledge of Docker and Kubernetes, plus proficiency with Bash, Python, or Terraform.
- Strong communication skills, attention to detail, and a collaborative, improvement-oriented approach.
Culture & Benefits
- Work in a small, nimble DevOps team with broad organizational impact.
- Collaborate across engineering, product, and security functions.
- Contribute to healthcare technology focused on improving data usability and outcomes.
- Inclusive workplace committed to equal employment opportunities and diverse perspectives.
- Human review remains part of the AI-supported recruitment process.
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