QA Engineer

Pune - India

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

QA Engineer - Job Description

Experience - 4 years

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 fundamentalsmetrics logs traces.
Exposure to infrastructure or SRE environments.
Basic knowledge of Kubernetes Docker or cloud platforms (AWS/GCP/Azure).

Required Experience:

QA Engineer - Job DescriptionExperience - 4 yearsKey ResponsibilitiesTest 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 ...

QA Engineer - Job Description

Experience - 4 years

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 fundamentalsmetrics logs traces.
Exposure to infrastructure or SRE environments.
Basic knowledge of Kubernetes Docker or cloud platforms (AWS/GCP/Azure).

Required Experience: