Applications Support Analyst

The Senior Application Support Analyst (C11) is a critical role responsible for ensuring the stability, reliability, and optimal performance of Citi's core business applications. This position requires a highly analytical and proactive professional who excels in Incident and Problem Management within an ITIL framework, combined with strong, hands-on technical expertise in Unix/Linux environments, SQL database querying, enterprise monitoring via ITRS Geneos, and batch workload scheduling via Autosys. Crucially, the successful candidate must have working experience supporting Big Data and EAP (Enterprise Application/Analytics Platform) environments, with a proven track record of driving automation and process enhancements to eliminate manual toil and optimize support workflows.

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 operations, such as daily health checks, application restarts, log archiving, and data reconciliation. Drive process improvements: Evaluate existing support workflows, runbooks, and escalation paths, implementing enhancements to streamline operations and reduce Mean Time to Repair (MTTR). 4. Incident Management & Production Recovery Own and drive the end-to-end resolution of L2/L3 production incidents, ensuring strict adherence to corporate Service Level Agreements (SLAs) and Service Level Objectives (SLOs). Lead technical triage during Major Incidents (MIM) and high-severity outages. Coordinate effectively with cross-functional global teams (Infrastructure, Database, Networks, Development, and Business Operations) to restore services rapidly. Act as the primary technical escalation point during incidents, translating complex technical issues into clear, concise, and business-friendly updates for senior leadership and stakeholders. Ensure accurate and timely logging, categorization, and tracking of incidents within ServiceNow. 5. Problem Management & Root Cause Analysis (RCA) Lead proactive Problem Management initiatives by analyzing incident trends, identifying systemic patterns, and