
SRE Analytics Analyst
1 day ago
Role & responsibilities
Performance & Capacity Planning
- Analyze system performance, resource utilization, and capacity trends to prevent bottlenecks.
- Provide recommendations for scaling infrastructure based on analytics.
Automation & Process Improvements
- Contribute to alert tuning, reducing false positives and improving signal-to-noise ratio.
- Assist in developing scripts and automation (Python, Shell, PowerShell, or equivalent) for repetitive operational tasks.
Monitoring & Observability
- Manage, configure, and optimize monitoring dashboards, alerts, and metrics (LogicMonitor, Datadog, Prometheus, Grafana, Splunk, etc.).
- Ensure proactive detection of system anomalies through trend analysis and predictive monitoring.
- Maintain SLOs, SLIs, and SLAs to ensure system reliability and performance.
Incident Management & Analytics
- Act as L2 support for production incidents, ensuring timely resolution or escalation to L3/SRE engineers.
- Perform root cause analysis (RCA) using logs, metrics, and traces, and provide detailed incident reports.
- Identify recurring issues through data analytics and recommend automation or process improvements.
Collaboration & Reporting
- Partner with SRE, DevOps, Application, and Infrastructure teams to resolve systemic issues.
- Generate regular reliability and performance reports for stakeholders.
- Share insights on service reliability, incidents, and optimizations with leadership and engineering teams.
Required Skills
- Strong experience with observability tools (LogicMonitor, Datadog, Grafana, Prometheus, ELK Stack, Splunk, etc.)
- Experience with time-series analysis (Prometheus, InfluxDB).
- Proficiency in scripting for monitoring/incident automation (Python, Shell, PowerShell, or similar)
- Experience in load testing tools for trend analysis
- Knowledge of trend and anomaly detection for proactive alerting
- Strong skills in data analysis with visualization tools (Grafana, Kibana, Power BI, Tableau).
- Proficiency in log analysis, metrics, and tracing frameworks.
- Working knowledge of cloud platforms (AWS, Azure, or GCP).
- Familiarity with container technologies (Docker, Kubernetes) and microservices monitoring.
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