Observability Engineer

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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,