QA Engineer - Job Description

Key Responsibilities

• Test product-specific use cases and validate end-to-end alerting workflows across monitoring systems.

• Simulate incidents and test scenarios that trigger alerts in tools like Datadog, Prometheus, or similar monitoring platforms.

• Verify that alerts raised in monitoring tools are correctly consumed and acted upon by downstream systems or automated workflows.

• Understand alert rules so test cases are easier to design, execute, debug, and maintain (alert configuration will be handled by Developers/SREs, but QA must understand them).

• Collaborate closely with engineering teams (Developers, SREs/DevOps) to improve detection, investigation, and automated incident response.

• Analyze alert behaviour, validate incident pipelines, and ensure seamless integration across all monitoring and automation tools.

• Identify gaps in monitoring, logging, and alert workflows and provide clear, actionable QA feedback.

• Document test scenarios, alert behaviour, and monitoring workflows in a clear and reproducible manner.

Mandatory Skills

• Monitoring Tools Expertise: Hands-on experience with at least one major monitoring system (Datadog or Prometheus), including working with alerts, dashboards, and troubleshooting.

• Alert Simulation & Validation: Ability to trigger, simulate, and validate alert events end-to-end.

• Incident Workflow Understanding: Strong understanding of how alerts propagate through monitoring systems and how automated systems respond to them.

• Automation Mindset: Ability to use or write simple scripts (Python, Shell, etc.) to simulate workloads or events that trigger alerts.

• Communication & Problem Solving: Ability to collaborate effectively with Developers and SRE/DevOps teams to ensure monitoring accuracy.

Good to Have

• Experience with automated incident investigation or remediation tools.

• Familiarity with CI/CD pipelines and integrating monitoring validation into pipelines.

• Understanding of observability fundamentals—metrics, logs, traces.

• Exposure to infrastructure or SRE environments.

• Basic knowledge of Kubernetes, Docker, or cloud platforms (AWS/GCP/Azure).