Observability Engineer

Observability Engineer – APAC
Location: Bengaluru (Bangalore), India
What this job involves:
As an Observability Engineer, you'll implement and operate enterprise monitoring and observability solutions across JLL's global technology infrastructure, with primary focus on Datadog. You'll bring fresh perspectives to existing monitoring approaches while independently solving complex infrastructure challenges that span multiple technology domains. Working with application, infrastructure, network, and cloud teams, you'll onboard services to monitoring, build insightful dashboards and intelligent alerts, troubleshoot telemetry pipelines, and create automation that improves operational efficiency.
At JLL, we believe the most effective teams are built when everyone is empowered to thrive, and this role offers an excellent opportunity to develop your skills while contributing to operational excellence. You'll independently design monitoring solutions for sophisticated use cases, evaluate existing implementations for improvement opportunities, and ensure solutions are scalable and maintainable. We embrace more innovative ways of working and prioritize opportunities to strengthen and advance your career, making this position ideal for an engineer who enjoys learning new technologies, solving technical problems, and growing expertise in observability practices.
What your day-to-day will look like:
Independent Design & Implementation:
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
Technical Problem Solving:
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
Automation & Best Practices:
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
Team Leadership & Collaboration:
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
AIOps & Innovation:
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
Required qualifications:
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; direct Datadog experience is strongly preferred with proven ability to design and implement solutions independently
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
Preferred qualifications:
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

Work arrangement
No