Observability Platform Engineer

About this role

Neuberger's Technology team is seeking an Observability Engineer to lead and evolve our observability strategy across cloud and on-premises environments. You will serve as the primary owner and subject matter expert for our Datadog platform — building, scaling, and operating a comprehensive monitoring solution that continuously validates service health (24/7) across business-critical systems, including external websites and key infrastructure components (e.g., firewalls, OpenShift). You will design and implement end-to-end observability solutions spanning logs, metrics, traces, Service Level Objectives (SLOs), synthetic monitoring, and Real User Monitoring (RUM) to improve reliability, accelerate incident response, and deliver clear visibility into service performance.

This is an individual contributor role with strong Datadog engineering and scripting expectations — not a pure administrator role, though prior admin experience is beneficial. You will partner closely with application, SRE/DevOps, infrastructure, and security teams and serve as the internal champion and evangelist for Datadog adoption, standards, and best practices. The environment includes an active migration from OpenView to Datadog, with workflows integrating into ServiceNow for incident routing and escalation. What You'll Do • Serve as the primary Datadog platform owner — architecting, building, and maintaining scalable observability solutions across cloud and on-prem environments (Windows and Linux/Unix), with direct ownership of monitoring capabilities for key applications and services.

• Partner closely with application, DevOps, SRE/operations, infrastructure, and security teams to translate reliability goals into actionable Datadog monitoring strategies, dashboards, SLOs, and alerting frameworks.

• Lead and execute the migration from OpenView to Datadog, ensuring continuity of coverage and an improvement in monitoring fidelity across all migrated services and infrastructure.

• Develop and automate processes using Datadog's APIs, Terraform provider, and scripting (Python, PowerShell, Bash) to manage monitors, dashboards, alerts, and telemetry configuration at scale — ensuring consistency across Windows Server and Unix (Linux/Solaris) environments.

• Implement and optimize Datadog APM, distributed tracing, log management, infrastructure monitoring, and Network Performance Monitoring (NPM) to provide full-stack visibility.

• Build and evolve Datadog RUM and Synthetic Monitoring capabilities to track end-user experience and proactively validate availability of external-facing services and critical workflows.

• Define and operationalize SLOs and error budgets within Datadog; drive alert noise reduction through correlation, enrichment, threshold tuning, and monitor dependency mapping.

• Integrate Datadog with ServiceNow for incident/problem ticket routing and escalation; produce runbooks, post-incident reviews, and executive/operational dashboards to support reliability reporting.

• Champion OpenTelemetry (OTel) adoption and drive consistent logging, metrics, and tracing standards across the engineering organization using Datadog as the central observability platform.

• Onboard new applications and services into Datadog; provide guidance and enablement to engineering teams on instrumentation, agent deployment, and observability best practices.

• Collaborate on platform cost optimization, data governance, and scaling strategies to ensure Datadog remains performant and cost-effective as the environment grows.

Required Skills and Experience • BS/BA in Computer Science, Information Systems, Engineering, or equivalent experience.

• 5+ years in Observability, APM, SRE, or Platform Engineering — with at least 2–3 years of hands-on, production-grade Datadog experience.

• Deep expertise across Datadog's core product suite: APM, Infrastructure Monitoring, Log Management, Synthetics, RUM, SLOs, Dashboards, Monitors, and Alerting.

• Proficiency in both Windows Server and Unix (Linux/Solaris) environments, including agent deployment, service instrumentation, and OS-level performance analysis.

• Strong scripting and automation skills (Python, PowerShell, Bash) with hands-on experience using the Datadog API/SDK and Terraform to manage observability configurations as code.

• Solid understanding of distributed tracing, metrics pipelines, logging standards, and SLO/error budget frameworks within Datadog.

• Experience integrating Datadog with cloud platforms (Azure and AWS) and centralizing cross-environment telemetry.

• Demonstrated ability to reduce alert noise and MTTR through Datadog monitor tuning, correlation, and enrichment strategies.

• Experience with ITSM integrations (e.g., Datadog → ServiceNow) and producing clear service maps, dependency views, and stakeholder-facing dashboards.

• Excellent communication and stakeholder management skills, with the ability to translate technical observability concepts for non-technical audiences.

• Strong documentation habits, attention to detail, and the ability to work both independently and collaboratively in a fast-paced environment.

Nice to Have • Datadog certifications (e.g., Datadog Fundamentals, APM, or Log Management).

• Experience migrating from legacy monitoring platforms (e.g., OpenView, AppDynamics, Nagios) to Datadog.

• Familiarity with .NET development (C#), including Datadog instrumentation patterns for .NET applications.

• Experience in financial services or other regulated industries.

• Familiarity with ITSM integrations and CMDB alignment for incident, problem, and change management workflows.

• Experience with CI/CD pipeline integration, synthetic testing strategies, and Datadog-based performance/capacity analysis for latency-sensitive systems.

• Knowledge of network monitoring concepts and Datadog NPM/NDM capabilities.

Hybrid Notice This is a hybrid position. Currently, the hybrid work schedule for this position is 2–3 days in the office. Pleas

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