Overview
On Site
Hybrid
Contract - W2
Skills
Dashboard
Performance Monitoring
Workflow
Slack
Management
Analytics
Predictive Analytics
Network
Performance Metrics
Mapping
Onboarding
API
Windows PowerShell
Problem Management
Root Cause Analysis
Operational Excellence
Testing
Optimization
Python
Scripting
Data Analysis
Reporting
Apache Kafka
Streaming
Grafana
Visualization
Artificial Intelligence
Amazon Web Services
IT Service Management
Event Management
ServiceNow
SNMP
NetFlow
Data Flow
Analytical Skill
Documentation
Communication
Collaboration
Job Details
Location: On-Site 3 days/week Orlando, FL preferred
Duration: 12+ month extendable contract
Job Summary
The Sr. Observability Engineer is responsible for designing, deploying, and optimizing client s enterprise observability ecosystem. This role delivers hands-on implementation and consulting expertise, focusing on LogicMonitor and modern observability practices to drive actionable insights, predictive analytics, and operational excellence across infrastructure, network, and application layers.
Key Responsibilities
Deploy, configure, and optimize LogicMonitor for enterprise-scale observability.
Design and build custom dashboards for actionable insights and performance monitoring.
Implement and manage data analytics workflows, including advanced scripting in Python for automation and reporting.
Integrate and manage data pipelines leveraging Kafka and related streaming technologies.
Ensure seamless data flow into Grafana for visualization and monitoring.
Develop and maintain integrations between observability, ITSM (ServiceNow), and event management tools (PagerDuty, Slack, BigPanda).
Standardize alert thresholds, escalation paths, and telemetry mappings across global regions.
Define and maintain event, alert, and rule logic to ensure accurate correlation and minimal noise.
Manage data ingestion pipelines from SNMP, syslog, APIs, and third-party sources into LogicMonitor and downstream analytics systems.
Advise on and implement AI-driven observability tools, including Amazon Bedrock, to enhance predictive analytics and anomaly detection.
Partner with network, server, and application teams to validate data flows, performance metrics, and dependency mapping.
Automate configuration and onboarding processes via API and scripting (Python, PowerShell, REST).
Support incident and problem management teams by correlating events across multiple tools to accelerate root cause analysis.
Document integrations, processes, and governance models for sustained operational excellence.
Serve as technical SME supporting observability tool upgrades, testing, and cross-platform enhancements.
Collaborate with stakeholders to align monitoring strategies with business objectives. Core Expertise & Skills
LogicMonitor platform deployment, configuration, and optimization.
Deep understanding of observability frameworks, best practices, and enterprise monitoring.
Python scripting for data analytics, automation, and advanced reporting.
Kafka-based data streaming and integration.
Grafana dashboarding and visualization.
Experience with AI platforms and emerging observability technologies, including Amazon Bedrock.
Familiarity with ITSM and event management systems (ServiceNow, PagerDuty, BigPanda).
Telemetry protocols (SNMP, syslog, NetFlow, APIs) and data flow architecture.
Strong understanding of alerting, correlation logic, and performance baselining.
Excellent analytical, documentation, and communication skills; ability to work across engineering and operations teams.
Duration: 12+ month extendable contract
Job Summary
The Sr. Observability Engineer is responsible for designing, deploying, and optimizing client s enterprise observability ecosystem. This role delivers hands-on implementation and consulting expertise, focusing on LogicMonitor and modern observability practices to drive actionable insights, predictive analytics, and operational excellence across infrastructure, network, and application layers.
Key Responsibilities
Deploy, configure, and optimize LogicMonitor for enterprise-scale observability.
Design and build custom dashboards for actionable insights and performance monitoring.
Implement and manage data analytics workflows, including advanced scripting in Python for automation and reporting.
Integrate and manage data pipelines leveraging Kafka and related streaming technologies.
Ensure seamless data flow into Grafana for visualization and monitoring.
Develop and maintain integrations between observability, ITSM (ServiceNow), and event management tools (PagerDuty, Slack, BigPanda).
Standardize alert thresholds, escalation paths, and telemetry mappings across global regions.
Define and maintain event, alert, and rule logic to ensure accurate correlation and minimal noise.
Manage data ingestion pipelines from SNMP, syslog, APIs, and third-party sources into LogicMonitor and downstream analytics systems.
Advise on and implement AI-driven observability tools, including Amazon Bedrock, to enhance predictive analytics and anomaly detection.
Partner with network, server, and application teams to validate data flows, performance metrics, and dependency mapping.
Automate configuration and onboarding processes via API and scripting (Python, PowerShell, REST).
Support incident and problem management teams by correlating events across multiple tools to accelerate root cause analysis.
Document integrations, processes, and governance models for sustained operational excellence.
Serve as technical SME supporting observability tool upgrades, testing, and cross-platform enhancements.
Collaborate with stakeholders to align monitoring strategies with business objectives. Core Expertise & Skills
LogicMonitor platform deployment, configuration, and optimization.
Deep understanding of observability frameworks, best practices, and enterprise monitoring.
Python scripting for data analytics, automation, and advanced reporting.
Kafka-based data streaming and integration.
Grafana dashboarding and visualization.
Experience with AI platforms and emerging observability technologies, including Amazon Bedrock.
Familiarity with ITSM and event management systems (ServiceNow, PagerDuty, BigPanda).
Telemetry protocols (SNMP, syslog, NetFlow, APIs) and data flow architecture.
Strong understanding of alerting, correlation logic, and performance baselining.
Excellent analytical, documentation, and communication skills; ability to work across engineering and operations teams.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.