Live opening · Posted 3 days ago
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Fully Remote
Datadog experience is most important as well as strong scripting experience.
Job Description
What this job involves:
As a Senior Observability Engineer, you'll play a pivotal role in building and supporting enterprise observability solutions across JLL's global technology estate, with a primary focus on Datadog. Working across infrastructure, network, cloud, and application environments, you'll improve visibility, automate monitoring and operational workflows, and help teams extract greater value from observability data. At JLL, we are collectively shaping a brighter way for our clients, ourselves and our fellow employees and your expertise will be instrumental in making operations smarter, faster, and more reliable. You'll collaborate with application, infrastructure, network, and cloud teams across APAC, AMER, and EMEA to understand their needs and implement effective monitoring solutions. This role offers the opportunity to work with cutting-edge AIOps and AI capabilities while solving complex technical problems and building automation that transforms how we deliver value. We embrace more innovative ways of working and prioritize opportunities to strengthen and advance your career, and this position is your chance to lead observability excellence in a globally distributed technology organization.
What Your Day-to-day Will Look Like
Build, configure, and optimize Datadog capabilities across infrastructure, applications, networks, cloud platforms, logs, and digital experience monitoring to provide comprehensive visibility
Develop dashboards, monitors, alerts, integrations, SLIs, SLOs, and service health views that deliver meaningful and actionable insights to stakeholders
Configure and troubleshoot Datadog agents, integrations, APIs, collectors, and telemetry pipelines to ensure reliable data collection and transmission
Build automation using Rundeck, Ansible, Python, PowerShell, APIs, and Git-based processes that simplifies observability onboarding, configuration, remediation, and ongoing platform operations
Apply observability-as-code practices to make monitoring configurations repeatable, scalable, and easier to maintain across environments
Configure and enhance AIOps capabilities including event correlation, anomaly detection, intelligent alerting, noise reduction, and incident enrichment to reduce operational burden
Leverage AI and generative AI capabilities to improve observability, troubleshooting, root-cause investigation, automation, and operational workflows
Integrate Datadog with enterprise platforms such as ServiceNow, Rundeck, cloud services, and CI/CD tooling to create seamless operational ecosystems
Use metrics, logs, traces, events, and network telemetry to investigate and resolve application and infrastructure performance issues, working collaboratively with teams across time zones
Required Qualifications
Bachelor's degree in Computer Science, Information Technology, Engineering, or related technical discipline, or equivalent combination of education and professional experience
5 8+ years of experience in observability, monitoring, Site Reliability Engineering (SRE), infrastructure engineering, application performance monitoring, or related enterprise technology roles
Strong hands-on experience implementing, configuring, and supporting Datadog in large-scale enterprise environments
Deep understanding of modern observability concepts including metrics, logs, traces, telemetry, distributed tracing, alerting, SLIs, and SLOs
Hands-on experience with automation and orchestration technologies such as Rundeck and Ansible
Proficiency in scripting and automation using Python, PowerShell, Bash, or similar languages
Experience working with REST APIs, webhooks, Git/GitHub, and CI/CD technologies
Experience with major cloud platforms, particularly Azure and AWS; GCP experience is beneficial
Familiarity with Infrastructure as Code (IaC) and configuration management practices
Preferred Qualifications
Experience with several observability domains including infrastructure monitoring, APM, logs, network monitoring, cloud monitoring, and digital experience monitoring
Hands-on experience with AIOps capabilities such as anomaly detection, event correlation, intelligent alerting, or automated incident analysis
Familiarity with generative AI and AI-assisted engineering, particularly applications that improve observability, automation, troubleshooting, and operational efficiency
Experience identifying opportunities to reduce alert noise, unnecessary telemetry, and platform consumption while maintaining visibility
Relevant certifications in Datadog, cloud technologies (AWS Certified Solutions Architect, Azure Administrator), automation, SRE, or related disciplines
Strong communication skills with demonstrated ability to work effectively in globally distributed teams and collaborate across APAC, AMER, and EMEA time zones
Work arrangement
Yes
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