Platform Engineer

Unisys; Rockville (MD); On-site; USD 180,000 - 240,000; Full time

Job summary

Unisys seeks a Kubernetes SME/Architect/Engineer to design, deploy, and operate mission-critical Amazon EKS infrastructure for petabyte-scale data processing. You will handle Kubernetes internals, large-scale cluster management, and Spark optimization to support thousands of concurrent jobs.

Responsibilities include configuring storage with EBS/EFS CSI drivers, managing spot and on-demand strategies, and enforcing resource quotas and priority classes in private networks.

Qualifications

• Deep Kubernetes expertise for scale and data-set processing.
• Strong SQL querying skills.
• Experience with Spark on Kubernetes for heavy workloads.

Responsibilities

• Design, deploy, and maintain production-grade Amazon EKS clusters for petabyte-scale data processing.
• Operate in air-gapped private VPC environments with secure repos and registries.
• Debug distributed systems across EKS, Karpenter, and Spark under heavy load.

Skills

Kubernetes expertise

Big data processing

SQL querying

Education

CKA, CKAD, CKS certifications

Tools

Amazon EKS

Apache Spark

Karpenter

EBS CSI

EFS CSI

Job description

Need a Kubernetes SME / Kubernetes Architect / Kubernetes Engineer with

• 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.
• Spark: Spark would be 50% of the work.
• SQL querying will assess on this as well.
• We are seeking an expert level Kubernetes Engineer to configure, deploy, and operate mission-critical Amazon EKS infrastructure supporting petabyte-scale data processing workloads.
• 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.

Core Responsibilities:

• Design, deploy, and maintain production-grade Amazon EKS clusters architected for petabyte-scale data processing with high availability and fault tolerance.
• Operate in air-gapped private VPC environments without internet access, managing secure package repositories and container registries.
• Debug and resolve complex distributed systems issues across EKS, Karpenter, and Spark, including scheduling bottlenecks, node scaling delays, and cascading failures under heavy load.
• Implement Karpenter consolidation and disruption policies balancing cost optimization with job resiliency.
• Manage spot and on-demand instance strategies with robust node interruption handling.
• Define and enforce ResourceQuotas, LimitRanges, and PriorityClasses to ensure fair resource distribution and prevent resource starvation.
• 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.
• Optimize storage configurations for resiliency, high-throughput data processing workloads.
• Implement logging, alerting, and anomaly detection to identify provisioning failures, executor loss, and throughput degradation before broader system impact.
• Design fault-tolerant architectures with retry strategies, checkpointing, and graceful degradation patterns minimizing re-computation on failure.
• Develop and manage configs in a private VPC without internet access.

Preferred Qualifications:

• Kubernetes Certifications (CKA, CKAD, or CKS) and AWS Certifications.
• Active contributions to open-source Kubernetes, Karpenter or Spark projects.
• Familiarity with FinOps practices and cost optimization at scale.
• Background in data engineering or analytics platforms.