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You’ll be part of our DevOps team that manages Kubernetes platforms in Azure and AWS. Your task will be to support all required activities for the migration from Azure/Azure DevOps pipelines to AWS/ GitHub Actions.
Requirements:
Experience: 5+ years of hands-on DevOps, platform engineering, or cloud infrastructure experience, including practical experience with Kubernetes-based application migrations and production-grade cloud environments.
Kubernetes and container platforms: Strong knowledge of Kubernetes, Docker, Helm and/or Kustomize, container image management, Kubernetes RBAC, service accounts, ingress controllers, workload troubleshooting, and operational support for production clusters.
AWS and EKS expertise: Strong hands-on experience with AWS services required for Kubernetes-based workloads, including EKS, IAM, IRSA, VPC networking, security groups, load balancers, Route 53, JFrog-based image registries, CloudWatch, Secrets Manager or Parameter Store, S3, RDS, and EFS where relevant.
Azure expertise: Solid hands-on experience with Azure services commonly involved in application migration, including AKS, Azure DevOps, Azure Container Registry, Azure networking, Azure identity, Key Vault, Azure Monitor, Log Analytics, and related platform integrations.
Infrastructure as Code: Expert-level Terraform experience is a must, including designing, building, refactoring, and maintaining infrastructure across Azure and AWS. Experience with reusable modules, remote state, environment separation, and infrastructure migration patterns is expected.
CI/CD: Expert-level experience with GitHub Actions is a must.
JupyterHub and JupyterLab (required for 1–2 out of 4 positions): Hands-on experience deploying and operating JupyterHub and JupyterLab at scale on Kubernetes in cloud environments (preferably AWS EKS). This includes experience with the Zero to JupyterHub Helm chart, spawner and authenticator customization (OAuth2/OIDC), persistent user storage configuration, resource quotas and auto-scaling of single-user notebook servers, GPU/compute-intensive workload support, and integration with cloud-native services (S3, EFS, IAM/IRSA). Familiarity with multi-tenant JupyterHub administration, user environment management, and observability of notebook workloads is expected.
Data and storage migration: Practical understanding of data and storage migration activities, including database migration planning, backup and restore, schema or service compatibility checks, cutover planning, rollback planning, data validation, and migration of persistent storage used by Kubernetes workloads.
Networking and connectivity: Strong understanding of cloud and Kubernetes networking, including VNet and VPC concepts, DNS, TLS certificates, ingress and egress traffic, firewall rules, private connectivity, load balancing, service discovery, and connectivity testing between Azure, AWS, and on-premises resources.
Security and compliance: Strong security mindset with experience mapping Azure identity and Kubernetes RBAC to AWS IAM and EKS access patterns, implementing least privilege, managing secrets securely, configuring workload identity, scanning container images, applying Kubernetes security best practices, and supporting audit and compliance requirements.
Observability and operations: Experience with monitoring, logging, alerting, and troubleshooting in Kubernetes and cloud environments, including CloudWatch, Azure Monitor, Log Analytics, Prometheus, Grafana, OpenTelemetry, application logs, metrics, traces, dashboards, and alert migration.
Scripting and automation: Proficiency in at least one scripting language such as Python or Bash, with the ability to automate migration tasks, validation checks, operational runbooks, and pipeline-related activities.
Nice to have:
AKS to EKS migration experience
Experience with migration from Azure DevOps YAML pipelines to GitHub workflows
Experience with JupyterHub and JupyterLab
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