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EXL

Analyzes business data and runs outsourced operations

Support Analyst

IT Service Desk & End User SupportConfirmed live in the last 24 hours
Full-timePune, Maharashtra, IndiaNo salary listed

About the Job

Requirements

  • Knowledge of the Hadoop ecosystem, including Oozie Workflow Manager, Apache Hive, and Apache Spark, for job monitoring, resubmission, and basic troubleshooting.
  • Familiarity with Apache Airflow for DAG monitoring, task failure identification, and manual trigger or rerun procedures.
  • Experience with Managed File Transfer tools for monitoring transfer jobs, identifying failures, and initiating reruns.
  • Working knowledge of Jenkins for pipeline monitoring, build status tracking, and failure alerting.
  • Understanding of AWS cloud services, including S3, EMR, CloudWatch, and EC2, in a data engineering context.
  • Experience using ServiceNow or similar IT service management platforms for ticket logging, triage, and workflow management.
  • Ability to read application and system logs, identify error patterns, and use command-line interfaces.
  • Two to four years of experience in IT operations or data platform support roles, with two or more years of hands-on data engineering experience.
  • Ability to work in a rotational 24×7 shift environment, including nights, weekends, and public holidays.
  • Ability to follow runbooks, standard operating procedures, and escalation protocols; document tickets and handoff notes clearly; and remain calm during high-severity P1/P2 incidents.
  • Comfort working with AI-assisted tools and adapting as automation evolves.

Responsibilities

  • Proactively monitor data pipelines, batch jobs, Oozie workflows, Airflow DAGs, Managed File Transfer transfers, and Jenkins jobs across platform components.
  • Respond to automated alerts within service-level agreement windows by validating, categorising, and actioning each alert using established runbooks.
  • Monitor Hadoop cluster health, including HDFS, YARN, Spark, and Hive; report anomalies and trigger job restarts or reruns according to standard operating procedures.
  • Perform job monitoring and report cloud resource-utilisation anomalies to the Lead.
  • Register and confirm incoming tickets in ServiceNow, acknowledging the issue logger within the service-level agreement of 15 minutes.
  • Categorise and prioritise tickets P1–P4 using the Incident Triage Matrix and route them to the correct resolution agent or support queue.
  • Perform initial troubleshooting using runbooks, the retrieval-augmented-generation knowledge base, and the FAQ repository; resolve known or routine issues without L2 escalation.
  • Escalate P1 incidents to L2 within 10 minutes with diagnostic context, including logs, error messages, job details, and steps already taken.
  • Manage incidents through closure by updating ticket status, documenting resolution steps, and closing tickets with accurate categorisation.
  • Transition incidents to P2/P3 teams when tiering changes and preserve full context during handover.
  • Prepare end-of-shift Daily Handoff Notes covering open incidents, in-progress issues, critical observations, and pending escalations.
  • Participate in shift-transition briefings with incoming analysts to support knowledge transfer and continuity of monitoring.
  • Document new issue patterns, resolutions, and lessons learned to enrich the knowledge base and support retrieval-augmented-generation updates.
  • Operate as a Human in the Loop within the EXLdata.ai Agentic framework by reviewing auto-triaged tickets, validating AI-suggested resolutions, and authorising automated remediation actions.
  • Provide feedback to the Agentic AI resolution and feedback agents to improve knowledge-base accuracy and auto-resolution rates.
  • Use AI CoPilot suggestions to assist with complex ticket handling and escalate to L2 when AI and L1 tooling cannot resolve an issue.

Desired Qualifications

  • ITIL Foundation certification, version 3 or 4.
  • Exposure to data observability tools such as Grafana, Prometheus, or CloudWatch.
  • Basic scripting skills in Python or Bash for log parsing and ad hoc data checks.
  • Experience in financial services or fintech data operations.

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1999

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