We are looking for an early-career professional to join our QRadar Support team (Charlie squad), focused on performance-related challenges. In this role, you’ll work directly with clients to troubleshoot complex issues involving the event pipeline, system performance, EPS (events per second), and rules processing. This position is highly technical and requires strong problem-solving skills, attention to detail, and the ability to investigate system bottlenecks and the curiosity to dive deeper as you grow in the role.
Serve as a primary point of contact for clients experiencing performance-related issues in QRadar
Investigate and resolve problems with the event pipeline, EPS rates, and rule performance
Analyze system metrics, logs, and configurations to identify bottlenecks or inefficiencies
Provide clear, step-by-step technical guidance to clients in English (written and verbal)
Collaborate with other squads, development, and operations teams on complex or escalated issues
Document troubleshooting steps and contribute to knowledge base articles to improve team efficiency
Participate in an on-call rotation or high-priority case management when required
Continuously build expertise in QRadar and performance tuning best practices
Intermediate Linux knowledge : navigating CLI, reading logs, monitoring processes, and troubleshooting performance issues
Experience troubleshooting software or infrastructure performance issues (e.g., CPU, memory, I/O bottlenecks, network impact)
Understanding of networking fundamentals (TCP/IP, ports, connectivity, DNS)
Analytical mindset with ability to investigate complex system behavior and interpret logs/metrics
Experience in a customer-facing technical support role or equivalent troubleshooting environment
Excellent communication skills in English (written and spoken)
Ability to stay calm under pressure and work through high-priority client issues
Familiarity with SIEM performance concepts: EPS (Events Per Second), event pipeline, rules performance
- Exposure to other SIEM platforms (e.g., Splunk, ArcSight, LogRhythm) or log management tools
Experience using monitoring or profiling tools (top, iostat, vmstat, nmon, etc.)
Knowledge of QRadar architecture or other enterprise-scale systems
Understanding of rules engines or workload optimization concepts
Basic scripting (Bash or Python) for troubleshooting and automation