QA Engineers Performance & Load Testing
Must Have Technical/Functional Skills
We are building a dedicated Performance Engineering squad for a high-scale, event-driven transactional platform. This role requires a senior-level specialist with deep expertise in performance and load testing. We are looking for top-tier candidates with proven experience validating scalability, reliability, and performance of distributed systems under heavy load. Hands-on performance and load testing experience is essential. We are seeking senior specialists, not generalist QA engineers. Familiarity with tools such as k6 (preferred), Locust, Gatling, distributed load generation, and modern observability stacks is required.
Mandatory Expectations
• Hands-on Performance & Load Testing experience is non-negotiable.
• We are seeking top-tier senior specialists, not generalist engineers.
• Deep expertise with k6 is preferred; experience with Locust, Gatling, or similar frameworks is required.
• Experience performing large-scale distributed load generation.
• Strong understanding of performance engineering principles including scalability, resiliency, throughput, latency analysis, and bottleneck identification.
• Hands-on experience with modern observability tooling including Grafana, Prometheus, Datadog, OpenTelemetry, distributed tracing, and APM platforms.
• Experience working with cloud-native, microservices-based, event-driven architectures.
• Proven ability to identify, analyze, and remediate complex performance issues across application, messaging, database, and infrastructure layers.
Technical Skills
• 7+ years of QA Engineering experience with 4+ years focused on Performance Engineering and Load Testing.
• Strong hands-on experience with k6, Locust, Gatling, JMeter, or equivalent performance testing tools.
• Experience designing and executing load, stress, endurance, spike, and scalability tests.
• Expertise testing HTTP/REST APIs, WebSockets, event-driven systems, Kafka, Pub/Sub, and messaging platforms.
• Strong understanding of latency analysis, throughput measurement, concurrency testing, error rate analysis, and capacity planning.
• Experience with distributed load generation and large-scale workload modeling.
• Proficiency with observability platforms including Grafana, Prometheus, Datadog, OpenTelemetry, and APM tools.
• Experience working with cloud-native and microservices-based applications.
• Scripting experience using Python, JavaScript, TypeScript, or similar languages.
Functional Skills
• Performance test strategy and planning.
• Workload modeling and performance benchmarking.
• Root cause analysis and bottleneck identification.
• Capacity planning and resiliency validation.
• Strong analytical and troubleshooting capabilities.
• Effective communication and stakeholder management.
• Cross-functional collaboration with Engineering, Infrastructure, and Product teams.
Roles & Responsibilities
• Design, develop, and execute comprehensive performance, load, stress, spike, and endurance testing strategies.
• Create realistic workload models and traffic patterns that reflect production usage.
• Execute performance testing across APIs, event streams, and real-time communication systems.
• Analyze latency percentiles (P95/P99), throughput, error rates, resource utilization, and overall system behavior.
• Identify and troubleshoot application, database, messaging, and infrastructure bottlenecks.
• Collaborate with development and infrastructure teams to validate remediation efforts.
• Define performance benchmarks and validate system scalability against SLAs.
• Develop automated performance testing solutions integrated into CI/CD pipelines.
• Produce detailed performance reports and recommendations to improve system reliability and scalability.
• Support release readiness assessments from a performance and scalability perspective.
Salary Range- $100,000-$120,000 a year
