Assignment description

We are looking for a Performance Test Engineer for a consulting assignment focused on ensuring that applications are scalable, stable and able to handle real-world demands.

In this role, you will be part of the QA team while working closely with development teams, team leads and architects to evaluate and optimize system performance. The assignment includes designing and executing performance, load, stress and scalability tests across APIs, end-to-end flows and infrastructure, as well as analysing results and providing actionable insights to improve reliability and efficiency.

You will work with integrating performance testing into CI/CD pipelines, defining and following up on performance baselines, SLAs and SLOs, and building dashboards to visualize performance trends, bottlenecks and system behaviour under different load conditions. The role also includes identifying performance issues, collaborating with development teams to optimize services and infrastructure, conducting capacity planning and scalability analysis, and producing reports and performance insights.

Tech stack:

• Backend: Java (Spring Boot microservices)
• Frontend: Vue 3
• Databases: Postgres (incl. Amazon Aurora), Redis
• Cloud infra: AWS (EKS, ECS, EC2, S3), Kubernetes, Terraform
• CICD: Jenkins, GitHub Actions

Qualifications:

• Several years of experience in Cloud infrastructure and tooling (AWS)
• Strong experience with tools like JMeter, k6, Taurus DLT
• Strong documentation skills (writing Post-Mortems, Performance Briefs, etc).
• Proven ability to automate non-functional checks (performance, accessibility, visual regression, DAST, etc.)
• Experience integrating tests into CI/CD (e.g. GitHub Actions, Jenkins)
• Ability to analyse metrics: latency, throughput, error rates
• Scripting skills (Java, JavaScript, Python, or similar)
• Understanding of: Distributed systems & microservices, REST APIs and async communication patterns as well as Observability tools (e.g. Elastic Stack / Kibana, CloudWatch)

Meriting:

• Experience with real user monitoring (RUM) and synthetic testing
• Security/performance overlap knowledge
• Experience with autoscaling validation in Kubernetes (EKS)
• Ability to read and modify Terraform configurations to provision test environments and tune infrastructure parameters (e.g., instance types, scaling policies) during performance bottlenecks analysis.