Description

Key Skills: Technical Support, Incident Management, Data Pipelines, Root Cause Analysis, Production Support, Monitoring & Alerting, Python, SQL, Debugging, Agile

Roles & 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

Key Skills

Education

Any Graduate