Observability Architect - Datadog

Hello,

Greeting of the day

Role - Datadog Platform & Observability Architect

Experience - 10+ Years

Notice Period - Immediate to 30 Days

Role Summary

We are seeking a Datadog Platform & Observability architect to design, implement, operate, and continuously improve our enterprise observability platform. This role enables engineering and operations teams to collect reliable telemetry, detect issues early, troubleshoot efficiently collaborating with Engineering teams, and manage observability governance and costs at scale.

Key Responsibilities

• Design, configure, and maintain Datadog monitors, dashboards, alerts, and integrations.
• Should have complete understanding of observability to build around Infra, Application and Network
• Should have exposure implementing Observability solutions for ERP and eComm applicaitons
• Should be able to effectively utilize AI modules of Datadog for auto detection and prevention
• Implement and support Infrastructure Monitoring, APM, Log Management, Synthetic Monitoring, RUM, and API monitoring.
• Configure application and infrastructure telemetry, including metrics, logs, traces, and events.
• Build and optimize Datadog log pipelines, parsing rules, indexes, retention filters, and enrichment.
• Configure and troubleshoot Datadog Agents across Windows, Linux, cloud, containers, and Kubernetes environments.
• Develop application-specific dashboards providing end-to-end visibility into application health and performance.
• Create proactive alerts for critical applications, APIs, infrastructure components, and business services.
• Review existing monitors and continuously improve alert thresholds, noise reduction, duplicate alerts, and actionable notifications.
• Support application teams with troubleshooting using logs, traces, metrics, and dependency information.
• Perform monitoring gap assessments and recommend improvements.
• Integrate Datadog with ITSM and collaboration platforms such as Ivanti, ServiceNow, Teams, Slack, or other enterprise tools.
• Support automation and event-driven incident creation/enrichment.
• Work with DevOps/SRE teams to implement monitoring-as-code using Terraform or similar tools.
• Participate in major incident troubleshooting and support RCA/problem management activities.
• Create and maintain SOPs, monitoring standards, technical documentation, and knowledge articles.
• Conduct knowledge-transfer sessions and help support teams effectively use Datadog for incident triage.
• Track monitoring effectiveness and demonstrate measurable improvements such as reduced alert noise, faster detection, lower MTTR, and fewer repeat incidents.

Required Technical Skills

• Strong hands-on experience with Datadog.
• Datadog Infrastructure Monitoring and Agent configuration.
• APM and Distributed Tracing.
• Log Management and Log Pipelines.
• Datadog dashboards, monitors, alerts, and notification configuration.
• Synthetic/API monitoring.
• Experience troubleshooting Windows and Linux systems.
• Good understanding of cloud platforms, preferably Azure and/or AWS.
• Knowledge of containers and Kubernetes monitoring.
• Understanding of REST APIs, JSON, and integration concepts.
• Scripting knowledge in Python, PowerShell, Bash, or similar languages.
• Experience with Terraform or Infrastructure-as-Code is preferred.
• Strong troubleshooting and root-cause analysis skills.
• Datadog RUM and Digital Experience Monitoring experience.
• Network monitoring experience.
• Azure Monitor / Log Analytics knowledge.
• Exposure to application performance optimization and capacity planning.

Good to Have

• Workato or other integration/automation platform experience.
• SRE/Observability implementation experience.
• CI/CD monitoring experience.
• ITIL knowledge covering Incident, Problem, and Change Management.

Key Expectations

The Architect should not only maintain existing monitoring but continuously identify opportunities to move operations from reactive support to proactive issue detection and prevention.

The person should be capable of independently identifying monitoring gaps, proposing solutions, implementing improvements, and working across multiple technical teams