Sr QA Engineer - NFR & Performance

Senior QA Engineer – NFR & Performance

Location: Hyderabad (Work from Office) | Type: Full-time | Experience: 4–5 years | Working Days: 5 Days a Week (Mon-Fri)

About Bluecopa

Bluecopa is an innovative finance operations automation platform that empowers modern finance teams to streamline operations, automate reconciliations, and gain real-time business insights. We're redefining how finance teams operate by bringing together technology, data, and financial expertise into a seamless product experience.

We are a fast-growing fintech backed by top-tier investors, serving high-growth companies with complex financial workflows. If you're passionate about transforming the quality and reliability of finance technology, Bluecopa is the place to be.

Position Overview

We are seeking a QA Engineer specializing in Non-Functional Testing to own performance, scalability, and resilience quality for the Bluecopa platform — a multi-tenant SaaS product running on Kubernetes. This role is not about validating features; it is about proving how the platform behaves under load, at scale, and in failure: sustained and peak traffic, large data volumes, concurrent tenants, pod restarts, autoscaling events, and degraded infrastructure.

The ideal candidate thinks in terms of throughput, latency, saturation, and failure modes rather than test cases — designing load models that mirror real production traffic, root-causing bottlenecks across the application, database, and Kubernetes layers, and turning findings into measurable NFR benchmarks the engineering team can hold releases to. You'll work closely with developers, DevOps/SRE, and fellow QA engineers to make scalability and reliability data-driven decisions, not guesswork.

Key Responsibilities

Performance & Load Testing

• Design, develop, and execute performance, load, stress, soak/endurance, spike, and scalability test plans for the platform's APIs, data pipelines, and heavy workflows.
• Build and maintain performance test scripts and reusable load models using tools such as JMeter, k6, Gatling, or LoadRunner.
• Define NFR benchmarks, SLAs/SLOs, and pass/fail acceptance criteria per release in collaboration with engineering and product teams.
• Simulate realistic production traffic patterns — multi-tenant concurrency, peak-load windows, and business-critical finance scenarios such as period close and high-volume reconciliations.

Scalability & Resilience on Kubernetes

• Validate platform behavior in Kubernetes under real operating conditions: horizontal pod autoscaling, rolling deployments under load, pod evictions and restarts, node failures, and resource limit/request boundaries.
• Test resilience and recovery — fault injection, dependency outages, connection-pool and queue saturation, and graceful degradation — and verify the platform contains and recovers from failures.
• Verify multi-tenant isolation under load: one tenant's heavy usage must not degrade performance or correctness for others.
• Assess capacity headroom and scaling limits of containerized services, and validate that autoscaling policies hold up against projected growth.

Monitoring, Analysis & Capacity Planning

• Monitor and analyze system resource utilization (CPU, memory, I/O, network) at the pod, node, and cluster level during test execution using APM and observability tools (Grafana, Prometheus, New Relic, Datadog, AppDynamics).
• Identify bottlenecks across application, database, and infrastructure layers, and drive them to root cause with engineering rather than one-off fixes.
• Conduct capacity planning analysis to forecast infrastructure needs based on projected growth and usage patterns.
• Verify observability coverage — that the metrics, logs, and alerts needed to detect the failure and saturation scenarios uncovered in testing actually exist.

Continuous Validation & Reporting

• Integrate performance and resilience test suites into CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, or similar) to catch regressions before release.
• Produce clear, actionable performance reports with metrics, trends, and recommendations for engineering and product stakeholders.
• Collaborate with developers and DevOps to tune application configurations, caching strategies, database queries, and Kubernetes resource settings for optimal performance.
• Participate in architecture and design discussions to proactively flag performance and scalability risks before they are built.

What We Are Looking For

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 4–5 years of hands-on QA experience with a demonstrated focus on non-functional testing — performance, load, scalability, and resilience — of SaaS or distributed platforms.
• Proven expertise in performance testing tools such as JMeter, k6, Gatling, or LoadRunner, including building load models from real traffic patterns.
• Strong understanding of NFR concepts — load, stress, soak/endurance, spike, scalability, and resilience testing — and how to set measurable acceptance criteria for each.
• Working knowledge of Kubernetes and containerized environments: how pods, autoscaling, resource limits, and deployments behave under load, and how to test against them.
• Experience analyzing system performance with APM and observability tools (Grafana, Prometheus, New Relic, Datadog, AppDynamics, or similar).
• Solid understanding of API behavior under load (REST) and experience testing API performance, concurrency, and rate limiting.
• Proficient in SQL for backend performance validation — analyzing slow queries and validating data-layer behavior under load.
• Working knowledge of at least one programming/scripting language (Java, JavaScript/TypeScript, Python, or Groovy) for building and customizing test harnesses.
• Experience with version control systems (Git) and CI/CD tools.

Preferred Qualifications

• Experience with cloud platforms (AWS, GCP, or Azure) and cloud-native performance testing at the cluster level.
• Exposure to chaos engineering and fault-injection tooling (Litmus, Chaos Mesh, Gremlin, or similar).
• Experience with distributed load generation and cloud-based load testing platforms (e.g., BlazeMeter, Azure Load Testing).
• Experience load-testing microservices-based and event-driven architectures, including message queues and streaming systems.
• Knowledge of database performance tuning, indexing strategies, and query optimization.
• Prior experience testing finance, fintech, or enterprise SaaS products.

Skills & Competencies

Technical Skills

• Performance and load testing tools (JMeter, k6, Gatling, LoadRunner)
• Kubernetes, Docker, and cloud-native service behavior under load
• Resilience, failover, and fault-injection testing
• APM and observability tools (Grafana, Prometheus, New Relic, Datadog, AppDynamics)
• SQL and database performance analysis
• API performance, concurrency, and rate-limit validation
• CI/CD pipelines and Git-based workflows
• Scripting in Java, JavaScript/TypeScript, Python, or Groovy

Soft Skills

• Strong analytical and root-cause problem-solving mindset
• Attention to detail — especially around performance metrics, saturation points, and edge-case load patterns
• Clear written and verbal communication, including reporting to non-technical stakeholders
• Self-motivated with the ability to work independently
• Collaborative team player who partners well with developers and DevOps/SRE
• Continuous learning mindset

What We Offer

• Competitive compensation package
• Opportunity to work with cutting-edge technologies
• Professional development and learning opportunities
• Flexible work arrangements
• Collaborative and innovative work environment
• Health and wellness benefits

We are an equal opportunity employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.