Senior Performance Test Engineer

We are looking for a Senior Performance Test Engineer with 7+ years of experience in SaaS applications, APIs, ETL pipelines, and cloud-native platforms with special focus on performance testing. The candidate will be responsible for performance testing, bottleneck analysis, scalability validation, and system optimization across distributed environments.

Spearhead End-to-End (E2E) performance testing and generate comprehensive metrics to evaluate system health. Design and deliver clear performance reports tailored for business stakeholders and clients. Mentor and guide junior team members to elevate overall team capabilities. Collaborate with cross-functional teams to identify and resolve critical performance bottlenecks .

Requirements

Key Responsibilities Design and execute load, stress, endurance, and scalability tests. Perform performance testing for: SaaS applications REST APIs Microservices ETL/Data pipelines Test Data Preparation as per API documentation and ETL transformation Synthetic data generation for database test Analyses application, database, and infrastructure bottlenecks.

Monitor system performance using APM and observability tools. Validate Kubernetes pod and cluster performance under varying workloads and suggest gaps and improvements. Work closely with DevOps, QA, and Engineering teams for performance tuning. Integrate performance tests into CI/CD pipelines.

Required Skills

Strong understanding of executing performance tests on: APIs Microservices ETL workflows SQL & NoSQL database performance Graph database (Neo4j, Neptune) performance Experience with Kubernetes, Docker, and cloud environments. Experience with Jenkins, Git, and CI/CD pipelines. Programming Languages: Proficiency in Java, Python, or Go for custom test scripting and log processing.

Testing Frameworks: Deep hands-on expertise with Apache JMeter, Gatling, Locust, or Load. Runner. APM & Observability: Mastery of monitoring tools like Dynatrace, App. Dynamics, Datadog, New Relic, Splunk, Grafana, and Prometheus. Architecture & Cloud: Strong understanding of distributed systems, Microservices, and cloud-native ecosystems (AWS, Azure).

Database Tuning: Experience analyzing query plans, locking mechanisms, and optimizing SQL/NoSQL databases Preferred Skills Cloud platforms: Amazon Web Services Microsoft Azure Google Cloud Kafka/Event-driven architecture exposure. Experience in Agile/Scrum environments.