Cloud Cost Optimization Engineer 17823

Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry. Assignment Description We are currently looking for an experienced Cloud Efficiency Engineer What You Will Work On Analyze infrastructure usage and identify cloud optimization opportunities Drive cost efficiency initiatives across cloud-native platforms Optimize Kubernetes resource allocation and workload placement Improve platform performance while maintaining service stability Execute rightsizing and autoscaling initiatives Troubleshoot resource contention and performance bottlenecks Optimize compute utilization and infrastructure consumption Analyze and improve JVM-based application performance Implement measurable cloud cost reduction initiatives Collaborate with engineering and data teams to support optimization programs Strengthen operational efficiency through automation and platform improvements Support long-term scalability and reliability objectives What You Bring Minimum 5 years of experience in cloud infrastructure engineering Proven hands-on experience with cloud cost optimization and resource efficiency Deep expertise in Google Cloud Platform or strong equivalent experience in AWS or Azure with readiness to work in GCP environments Strong understanding of cloud compute models, pricing structures, and infrastructure utilization Extensive experience optimizing Kubernetes / GKE workloads in large-scale environments Experience with rightsizing, autoscaling, and troubleshooting resource contention Strong Java knowledge and experience supporting JVM-based services Practical experience with GC log analysis, heap tuning, and runtime optimization Demonstrated ability to implement measurable optimization initiatives Strong understanding of balancing performance improvements with reliability and stability requirements Structured and data-driven approach to infrastructure decision-making