Key Responsibilities
1. Big Data & EAP (Enterprise Application/Analytics Platform) Support
Support Distributed Environments: Provide Level 2 (L2) and Level 3 (L3) support for applications hosted on Big Data platforms and Citi's Enterprise Application/Analytics Platform (EAP).
Troubleshoot Data Pipelines: Diagnose and resolve failures in complex data ingestion and processing pipelines, including distributed processing frameworks (e.g., Apache Spark, Hadoop MapReduce).
Cluster & Resource Monitoring: Monitor cluster resource utilization (using YARN, Cloudera Manager, or similar tools) to identify and resolve memory bottlenecks, queue congestion, and job failures (e.g., Spark Out-Of-Memory errors).
Data Querying & Validation: Query and validate large-scale datasets stored in distributed data warehouses and file systems (e.g., HDFS, Hive, Impala, or HBase).
Message Queue Management: Monitor and troubleshoot real-time streaming and messaging platforms (e.g., Apache Kafka), managing consumer groups, offsets, and partition lags.
2. Batch Management & Job Scheduling (Autosys)




Monitor and manage batch execution: Oversee the execution of critical daily, weekly, and monthly batch processing cycles scheduled via Autosys.
Troubleshoot batch failures: Rapidly diagnose and resolve Autosys job failures, analyzing log files, identifying dependency issues, and performing necessary job overrides, force-starts, or hold/release actions to minimize business impact.
Optimize job flows: Collaborate with development and engineering teams to define, configure, and optimize Autosys job definitions using JIL (Job Information Language).
3. Automation & Process Enhancement (Toil Reduction)
Identify and eliminate manual bottlenecks: Actively analyze daily support activities to identify repetitive, manual tasks ("toil") and design automated solutions to eliminate them.
Develop automation scripts: Write, test, and deploy robust scripts (using Python, Bash, or PowerShell) to automate routine operatio

📌 Production Support Genesis (India)
🏢 Citi
📍 India