Description

• Design, deploy, and maintain highly available Amazon EKS clusters supporting large-scale data processing workloads.
• Build and operate secure Kubernetes environments within private AWS VPCs, including air-gapped deployments, private container registries, and internal package repositories.
• Troubleshoot complex Kubernetes, Karpenter, and distributed application issues including scheduling, autoscaling, networking, and cluster performance.
• Optimize node provisioning using Karpenter, balancing workload performance, resiliency, and cloud cost optimization.
• Design and implement strategies for Spot and On-Demand capacity management, including graceful interruption handling and workload recovery.
• Configure Kubernetes resource management using ResourceQuotas, LimitRanges, PriorityClasses, taints, tolerations, and affinity rules to maximize cluster efficiency.
• Deploy and optimize persistent storage solutions using Amazon EBS CSI and Amazon EFS CSI drivers for high-performance data processing workloads.
• Build observability solutions with centralized logging, monitoring, alerting, and performance dashboards to proactively identify issues before production impact.
• Design resilient platform architectures utilizing checkpointing, retry mechanisms, fault isolation, and automated recovery strategies.
• Partner with platform, infrastructure, and data engineering teams to improve scalability, automation, security, and operational excellence.

Required Qualifications

• 8+ years of infrastructure, cloud engineering, or platform engineering experience.
• Deep expertise administering Kubernetes in large-scale production environments.
• Strong experience designing and operating Amazon EKS clusters.
• Experience with Kubernetes autoscaling technologies including Karpenter or Cluster Autoscaler.
• Strong understanding of Kubernetes scheduling, networking, storage, security, and cluster lifecycle management.
• Experience supporting Apache Spark or other distributed compute frameworks in Kubernetes environments.
• Hands-on experience with AWS services including EC2, EBS, EFS, IAM, VPC, CloudWatch, and Auto Scaling.
• Experience operating highly available, production-critical systems with a focus on performance, resiliency, and automation.
• Strong scripting or programming experience using Python, Go, or Bash.
• Experience implementing Infrastructure as Code using Terraform, CloudFormation, or similar technologies.
• Strong troubleshooting skills across distributed systems and cloud-native infrastructure.

Preferred Qualifications

• Kubernetes certifications (CKA, CKAD, or CKS).
• AWS Certified Solutions Architect or AWS Certified Kubernetes-related certifications.
• Experience operating air-gapped or highly secure cloud environments.
• Contributions to Kubernetes, Karpenter, Spark, or other cloud-native open-source projects.
• Experience implementing FinOps and cloud cost optimization strategies.
• Background supporting large-scale data engineering, analytics, or AI/ML platforms.
• Familiarity with GitOps tools such as ArgoCD or Flux

Key Skills

Education

Bachelor's degree