Platform Engineer

Job Description

Need a Kubernetes SME / Kubernetes Architect / Kubernetes Engineer with

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• Deep Kubernetes experience (Troubleshooting, configuring for scale), doing this at scale involves working with larger data sets (aka Big Data) and they use Spark on Kubernetes to run their processes.

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• Spark: Spark would be 50% of the work.

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• SQL querying will assess on this as well.

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Senior Kubernetes Engineer Overview:

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• We are seeking an expert level Kubernetes Engineer to configure, deploy, and operate mission-critical Amazon EKS infrastructure supporting petabyte-scale data processing workloads.

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• This role requires deep technical expertise in Kubernetes internals, large-scale cluster management, and Apache Spark optimization to support thousands of concurrent jobs processing large volumes of Bigdata.

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Core Responsibilities:

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• Design, deploy, and maintain production-grade Amazon EKS clusters architected for petabyte-scale data processing with high availability and fault tolerance.

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• Operate in air-gapped private VPC environments without internet access, managing secure package repositories and container registries.

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• Debug and resolve complex distributed systems issues across EKS, Karpenter, and Spark, including scheduling bottlenecks, node scaling delays, and cascading failures under heavy load.

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• Implement Karpenter consolidation and disruption policies balancing cost optimization with job resiliency.

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• Manage spot and on-demand instance strategies with robust node interruption handling.

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• Define and enforce ResourceQuotas, LimitRanges, and PriorityClasses to ensure fair resource distribution and prevent resource starvation.

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• Configure persistent volume claims and provision container-native storage using Amazon EBS CSI driver for block storage and Amazon EFS CSI driver for shared file access.

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• Optimize storage configurations for resiliency, high-throughput data processing workloads.

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• Implement logging, alerting, and anomaly detection to identify provisioning failures, executor loss, and throughput degradation before broader system impact.

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• Design fault-tolerant architectures with retry strategies, checkpointing, and graceful degradation patterns minimizing re-computation on failure.

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• Develop and manage configs in a private VPC without internet access.

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Preferred Qualifications:

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• Kubernetes Certifications (CKA, CKAD, or CKS) and AWS Certifications.

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• Active contributions to open-source Kubernetes, Karpenter or Spark projects.

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• Familiarity with FinOps practices and cost optimization at scale.

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• Background in data engineering or analytics platforms.

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#LI-CGTS

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#TS-3142