Performance Quality Engineer
New
Based in United StatesFull-TimeMiddle
Salary$120,000–$165,000
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Job Details
- Experience
- 3+ years
- Required Skills
- AWSDockerPythonKubernetesGrafanaPrometheusCI/CDDatadog
Requirements
- 3+ years of hands-on experience in performance testing and analysis for microservices-based, cloud-hosted SaaS platforms.
- Strong analytical skills with the ability to identify root causes behind complex performance issues.
- Experience with statistical analysis, including trend modeling, interpolation, extrapolation, and capacity forecasting.
- Working knowledge of AWS services such as EC2, RDS, S3, ECS/EKS, along with Docker and Kubernetes.
- Experience using performance testing tools such as k6, Gatling, Locust, JMeter, or similar technologies.
- Familiarity with observability platforms including Prometheus, Grafana, Datadog, and log aggregation tools such as ELK Stack or CloudWatch.
- Proficiency in Python or another scripting language for test automation, data analysis, and tooling improvements.
- Understanding of CI/CD workflows and experience integrating performance validation into development pipelines.
- Ability to collaborate effectively in a remote-first, asynchronous environment across multiple time zones.
- Experience using AI tools and technologies to improve workflows, decision-making, and engineering productivity.
- Strong communication skills with the ability to present technical insights clearly to engineering and product stakeholders.
Responsibilities
- Design and develop performance test suites for multiple product teams supporting a microservices-based SaaS platform hosted on AWS.
- Operate and maintain production-like environments used for performance analysis, diagnostics, and regression testing.
- Analyze application and infrastructure logs to identify performance issues and support root-cause investigations.
- Define, monitor, and report performance KPIs, including response times, throughput, error rates, and resource utilization.
- Deliver trend analysis, capacity forecasts, and actionable recommendations to engineering leaders and product stakeholders.
- Identify potential scalability risks through usage and performance data before they affect customers.
- Collaborate with Platform Engineering, DevX, SDET, Security QE, and Product teams to validate and prioritize performance improvements.
- Partner with security teams to incorporate security-informed scenarios into performance testing, including stress testing and resource utilization analysis.
- Establish performance testing standards within CI/CD pipelines by defining quality gates, thresholds, and regression detection processes.
- Create documentation, runbooks, and best practices to strengthen performance engineering capabilities across the organization.
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