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We are seeking a highly skilled and proactive engineer with strong experience in Control -M, AppDynamics, and Splunk development, combined with solid scripting capabilities. The ideal candidate will be responsible for job scheduling, system monitoring, performance analysis, observability enhancements, and automation across enterprise environments.
Design, develop, and maintain Control -M job workflows and schedules.
Optimize batch processes and troubleshoot job failures or delays.
Create and manage job templates, calendars, and dependencies.
Integrate Control -M with APIs, scripts, and external systems.
Assist with environment upgrades, patches, and configuration changes.
Configure, implement, and maintain AppDynamics APM agents across applications.
Build dashboards, alerts, and health rules to ensure proactive monitoring.
Analyze performance issues using AppDynamics tools (flow maps, node snapshots, transaction tracking).
Collaborate with application and infrastructure teams to resolve bottlenecks.
Create and optimize SPL queries, dashboards, alerts, and reports.
Develop data onboarding pipelines, parsing rules, and field extractions.
Work with various log sources to improve system observability.
Implement best practices for data retention, indexing, and search efficiency.
Develop automation scripts using Python, Shell, PowerShell, or Perl.
Automate repetitive tasks such as log processing, monitoring enhancements, and report generation.
Integrate scripts with Control -M, Splunk, and monitoring workflows.
7+ years of hands -on experience with Control -M batch scheduling.
Strong proficiency in AppDynamics configuration, dashboards, and performance analysis.
Hands -on experience with Splunk dashboards, SPL queries, and data onboarding.
Strong scripting skills (Python, Shell, PowerShell, or similar).
Understanding of application logs, performance metrics, and distributed systems.
Experience working in Linux/Unix and/or Windows environments.
Strong analytical, debugging, and problem -solving skills.
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