DevOps Engineer New
Role details
Job location
Tech stack
Job description
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Infrastructure Management: Provision, maintain, and upgrade AWS and EKS infrastructure using tools like kubectl, Kustomize, and Helm.
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Automation & IaC: Develop and document reusable Terraform and Terragrunt modules to automate deployments, backups, and routine maintenance.
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CI/CD & GitOps: Build and refine CI/CD pipelines using GitHub Actions and GitOps workflows, specifically leveraging ArgoCD (including app-of-apps and ApplicationSets).
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Monitoring & Reliability: Monitor performance and logs via DataDog and AWS CloudWatch, troubleshoot incidents, and take full ownership of the long-term reliability of the systems you build.
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Data Platform Support: Support data engineers by operating and improving data platforms or data-adjacent infrastructure (e.g., Airflow/MWAA, SQLMesh) in production environments.
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Streaming Systems: Support and maintain streaming or real-time data systems to ensure consistent data flow and system uptime.
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Cost Optimization: Analyze cloud spend using AWS Cost Explorer and Infracost to identify waste and implement cost-saving measures.
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Operational Support: Assist developers with daily operational needs and maintain security/RBAC and resource efficiency within Kubernetes environments.
As a DevOps Engineer, you are responsible for maintaining and optimizing our AWS and Kubernetes infrastructure to ensure high reliability, security, and scalability. You will focus on driving cost efficiency, accelerating deployment cycles for developers, and piloting emerging tools that deliver measurable value to the organization.
Requirements
Do you have experience in Terraform?, * Kubernetes: Production-level experience with EKS, including Helm and Kustomize.
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Infrastructure as Code: Proficiency in Terraform and Terragrunt.
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Cloud & Data Systems: Hands-on experience with the AWS Ecosystem (EC2, ECR, RDS, MSK) and experience operating production data platforms or streaming systems.
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GitOps: Proven experience with ArgoCD and GitHub Actions automation.
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Tools: Familiarity with DataDog, MongoDB, and AI-assisted tools like Claude CLI or GitHub Copilot.
Attributes: An intrinsic desire to learn and fill in missing skills, with a proactive approach to conducting proof-of-concepts for new DevOps practices.