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Support Analyst

EXL
Pune, IND
Junior · 2–4 years experience
Hybrid
Discovered 1 weeks ago
airflowawsbashcloudwatchgrafanahadoop
Free

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Responsibilities

  • Monitoring & Alerting
  • Proactively monitor data pipelines, batch jobs, Oozie workflows, Airflow DAGs, MFT transfers, and Jenkins jobs across all platform components.
  • Respond to automated alerts within SLA windows; validate, categorise, and action each alert using established runbooks.
  • Monitor Hadoop cluster health (HDFS, YARN, Spark, Hive); report anomalies and trigger job restarts/reruns per standard operating procedures.
  • Perform job monitoring and report cloud resource utilisation anomalies to the Lead.
  • Incident Management & Triage
  • Register and confirm all incoming tickets in ServiceNow; acknowledge the issue logger within SLA (<15 minutes).
  • Categorise and prioritise tickets (P1–P4) using the Incident Triage Matrix; route to the correct resolution agent or support queue.
  • Perform initial troubleshooting using runbooks, RAG-enabled knowledge base, and FAQ repository; resolve known/routine issues without L2 escalation.
  • Escalate P1 incidents to L2 within 10 minutes with complete diagnostic context — logs, error messages, job details, and steps already taken.
  • Manage incident workflow through to closure; update ticket status, document resolution steps, and close with accurate categorisation.
  • Transition incidents to P2/P3 teams upon tiering changes; ensure smooth handover with full context preserved.
  • Shift Handover & Documentation
  • Prepare comprehensive Daily Handoff Notes at end of shift: open incidents, in-progress issues, critical observations, and pending escalations.
  • Participate in shift-transition briefings with incoming analysts to ensure seamless knowledge transfer and continuity of monitoring.
  • Contribute to knowledge base enrichment by documenting new issue patterns, resolutions, and lessons learned to support RAG-based knowledge updates.
  • Agentic AI Collaboration (HITL)
  • Operate as Human in the Loop (HITL) within the EXLdata.ai Agentic framework: review auto-triaged tickets, validate AI-suggested resolutions, and authorise automated remediation actions.
  • Provide feedback to the Agentic AI resolution and feedback agents to improve knowledge base accuracy and auto-resolution rates over time.
  • Utilise AI CoPilot suggestions to assist with complex ticket handling; escalate to L2 when AI and L1 tooling cannot resolve the issue.
  • Monitoring & Alerting - Proactively monitor data pipelines, batch jobs, Oozie workflows, Airflow DAGs, MFT transfers, and Jenkins jobs across all platform components. - Respond to automated alerts within SLA windows; validate, categorise, and action each alert using established runbooks. - Monitor Hadoop cluster health (HDFS, YARN, Spark, Hive); report anomalies and trigger job restarts/reruns per standard operating procedures. - Perform job monitoring and report cloud resource utilisation anomalies to the Lead. Incident Management & Triage - Register and confirm all incoming tickets in ServiceNow; acknowledge the issue logger within SLA (<15 minutes). - Categorise and prioritise tickets (P1–P4) using the Incident Triage Matrix; route to the correct resolution agent or support queue. - Perform initial troubleshooting using runbooks, RAG-enabled knowledge base, and FAQ repository; resolve known/routine issues without L2 escalation. - Escalate P1 incidents to L2 within 10 minutes with complete diagnostic context — logs, error messages, job details, and steps already taken. - Manage incident workflow through to closure; update ticket status, document resolution steps, and close with accurate categorisation. - Transition incidents to P2/P3 teams upon tiering changes; ensure smooth handover with full context preserved. Shift Handover & Documentation - Prepare comprehensive Daily Handoff Notes at end of shift: open incidents, in-progress issues, critical observations, and pending escalations. - Participate in shift-transition briefings with incoming analysts to ensure seamless knowledge transfer and continuity of monitoring. - Contribute to knowledge base enrichment by documenting new issue patterns, resolutions, and lessons learned to support RAG-based knowledge updates. Agentic AI Collaboration (HITL) - Operate as Human in the Loop (HITL) within the EXLdata.ai Agentic framework: review auto-triaged tickets, validate AI-suggested resolutions, and authorise automated remediation actions. - Provide feedback to the Agentic AI resolution and feedback agents to improve knowledge base accuracy and auto-resolution rates over time. - Utilise AI CoPilot suggestions to assist with complex ticket handling; escalate to L2 when AI and L1 tooling cannot resolve the issue.

Qualifications

  • Graduate in Computer Science, B.Tech, B.E with 2+ years of hands-on data engineering experience.

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