Job Specifications
QA Engineer - Live Monitoring POD
The successful candidate will play a critical role in ensuring the continuous health, performance, and reliability of our live production systems, with a focus on immediate defect detection and operational quality.
Live Production Health Validation: Design, implement, and maintain Synthetic Monitoring Tests and automated Production Health Checks that run continuously against the live system to simulate real user journeys and validate key business flows.
Observability and Triage: Monitor, analyze, and interpret performance and quality metrics from live monitoring tools (e.g., Datadog, Prometheus, Splunk). Rapidly triage and diagnose alerts to determine root cause, scope, and business impact.
Operational Quality Assurance: Validate the accuracy of data flows by performing advanced log analysis (e.g., with Splunk or Kibana) and conducting SQL queries on production databases to ensure data integrity following live events.
Automation for Reliability: Build and integrate automated checks into the CI/CD pipeline to serve as a final, reliable quality gate before and after deployments. Maintain and evolve the core automation framework (using tools like Cypress, Playwright, etc.).
Incident Management & Reporting: Act as the first line of QA during major incidents, providing clear, data-driven analysis to the incident management team and ensuring that all production defects are thoroughly documented and retested post-fix.
Proactive Quality Improvement: Collaborate with SRE and Development teams to establish and enforce SLIs (Service Level Indicators) and SLOs (Service Level Objectives) related to system performance and availability.
Required Skills & Qualifications (Emphasizing Operational Tech Stack)
8+ years of hands-on experience in software quality assurance, with at least 2 years of recent experience in a production/live operations environment (Live Monitoring, SRE, or DevOps QA).
Deep Proficiency in Observability Tools: Strong experience with at least one major APM/Log Management tool (e.g., Datadog, Splunk, Kibana, Grafana, New Relic). Ability to create complex queries, custom dashboards, and actionable alerts.
Automation Expertise: Proficiency in building and maintaining robust test automation frameworks using Java, JavaScript (Node.js), or Python and tools like Cypress or Playwright for reliable synthetic testing.
Data Validation and Back-End Skills: Expert-level knowledge of SQL for data validation and strong experience with API testing (e.g., Postman, Rest Assured) to check the health of back-end services.
SDLC/Agile Fluency: Excellent understanding of modern development practices, including Agile/Scrum, DevOps, CI/CD integration (Jenkins/GitHub Actions), and effective use of defect tracking tools (Jira).
Performance Validation in Live Context: Understanding of key performance metrics (latency, error rates, throughput) and experience correlating performance data with quality outcomes.
About the Company
Orion Innovation is a global leader powered by Data and AI, helping businesses innovate, scale, and adopt future technologies in an increasingly dynamic world.
With deep expertise in digital experiences and engineering, Orion drives sustainable growth by delivering GenAI, Cloud, and Digital Experience solutions that combine cutting-edge technology, strategy, and engineering to create real business impact. We partner with leading organizations across diverse industries, including Telecom & Technology, Industrial & Consumer ...
Know more