Observability Engineer

Overview

Implement and operate enterprise monitoring and observability solutions across JLL's global technology infrastructure, with primary focus on Datadog.

What you'll do

• Design and configure comprehensive Datadog monitoring solutions independently across infrastructure, applications, networks, cloud platforms, logs, and digital experience capabilities aligned with enterprise standards
• Create and maintain well-designed dashboards, monitors, alerts, integrations, and service health views that provide actionable visibility into system performance and health
• Evaluate and enhance existing monitoring implementations, identifying opportunities to improve reliability, reduce operational overhead, and increase observability effectiveness
• Independently solve moderately complex to complex infrastructure and application monitoring challenges by analyzing metrics, logs, and traces while applying established methodologies
• Install, configure, validate, and troubleshoot Datadog agents, integrations, APIs, collectors, and telemetry pipelines to ensure consistent and reliable data collection
• Use comprehensive telemetry including metrics, logs, distributed traces, events, and network data to diagnose and resolve application and infrastructure issues
• Build and maintain production-grade automated workflows using tools such as Rundeck, Ansible, Python, PowerShell, APIs, and Git-based processes
• Apply observability-as-code principles and automation patterns to make monitoring configurations consistent, version-controlled, repeatable, and easier to maintain across environments
• Identify and implement innovative automation solutions using AI-assisted approaches for operational tasks, reducing manual effort and improving consistency
• Onboard services and implement monitoring solutions by collaborating directly with application, infrastructure, network, and cloud teams to understand requirements and constraints
• Serve as a technical resource for less experienced colleagues on troubleshooting techniques, operational procedures, and monitoring best practices
• Lead moderately sized projects with defined scope and act as an informal mentor, delivering knowledge-sharing sessions on incident response, system design, and observability principles
• Coordinate incident response activities and communicate complex technical information clearly to stakeholders across different technical backgrounds
• Support and enhance AIOps capabilities including event correlation, anomaly detection, intelligent alert routing, noise reduction, and incident enrichment
• Leverage AI and AI-assisted engineering tools to accelerate troubleshooting, improve automation quality, enhance documentation, and optimize operational workflows
• Contribute improvements to system reliability and operational efficiency by applying modern observability practices within established enterprise frameworks

What you'll need

• Bachelor's degree in Computer Science, Information Technology, Engineering, or related technical discipline, or equivalent combination of education and professional experience
• 3–5+ years of experience in observability, monitoring, infrastructure engineering, application support, Site Reliability Engineering (SRE), or related technology roles with demonstrated ability to work independently on complex challenges
• Strong hands-on experience with Datadog or comparable enterprise observability platforms
• Solid working knowledge of observability concepts including metrics, logs, traces, telemetry, alerting, service health, and reliability principles with ability to apply them effectively
• Demonstrated experience with automation and orchestration tools such as Rundeck and Ansible, with expanding skillset in operational automation
• Proficient scripting experience using Python, PowerShell, Bash, or similar languages with ability to create maintainable, production-quality automation
• Practical experience working with REST APIs, webhooks, Git/GitHub, and CI/CD technologies with understanding of integration patterns and workflows
• Solid exposure to cloud platforms such as Azure, AWS, or GCP with proficiency in cloud-native technologies and end-to-end reliability solution implementation

Nice to have

• Direct Datadog experience with proven ability to design and implement solutions independently
• Experience across multiple observability areas such as infrastructure monitoring, application performance monitoring, log analytics, network monitoring, cloud monitoring, or digital experience monitoring
• Familiarity with Infrastructure as Code (IaC), configuration management, and configuration-as-code practices with understanding of observability-as-code principles
• Experience supporting integrations between observability platforms and enterprise systems such as ServiceNow, Rundeck, cloud services, or CI/CD tooling
• Demonstrated exposure to AIOps concepts and AI-assisted engineering tools with practical understanding of their applications in observability and operations
• Relevant certifications in Datadog, cloud platforms (AWS, Azure, GCP), automation frameworks, or related technical areas
• Demonstrated ability to create and maintain technical documentation, follow established operational procedures and standards, and communicate technical concepts effectively to diverse audiences
• Proven ability to build strong working relationships across operational teams and collaborate effectively in globally distributed, culturally diverse environments

Details

• Location: Bengaluru (Bangalore), India, on-site
• Scheduled weekly hours: 40