Job Title

Company:Global Banking OrganizationKey Skills: Technical Support, Incident Management, Data Pipelines, Root Cause Analysis, Production Support, Monitoring & Alerting, Python, SQL, Debugging, AgileRoles & Responsibilities:Provide L3 support for complex production issues across analytics platforms, data pipelines, and reporting workflows in Production, UAT, and Development environments. Perform advanced root cause analysis across data ingestion, transformation logic, storage layers, and downstream systems. Design and implement fixes, patches, and workarounds to restore data integrity, availability, and performance. Validate and monitor fixes post-deployment to ensure complete resolution and prevent recurrence. Act as the primary escalation point for L1/L2 teams during high-severity or complex incidents. Collaborate with Analytics Support Leads during Sev 1 and Sev 2 incidents to drive resolution strategies. Provide clear technical assessments, impact analysis, and risk evaluations to stakeholders. Identify systemic issues and weaknesses in analytics platforms and data pipelines. Enhance observability by improving logging, monitoring, alerting, and diagnostics. Document root causes, resolutions, and recurring issue patterns for knowledge sharing. Participate in post-incident reviews and technical retrospectives for continuous improvement. Drive automation and optimization initiatives to reduce manual intervention and recurring issues. Support performance tuning and scalability improvements for analytics systems. Mentor L1/L2 support teams and provide guidance on complex issue handling. Experience Required:6 - 9 years of experience in production support, analytics support, or technical support roles. Strong experience in handling complex incident management and escalation scenarios. Hands-on experience with data pipelines, ETL processes, and analytics platforms. Proficiency in debugging and root cause analysis across distributed systems. Experience with monitoring and alerting tools for production environments. Working knowledge of Python and SQL for troubleshooting and data validation. Experience working in SLA-driven, high-availability environments. Familiarity with Agile and DevOps practices is an added advantage. Education: Any Graduation