Job Summary
The Platform Observability Engineer will implement Datadog-based observability patterns across services, infrastructure, and platform telemetry. This role focuses on practical dashboarding, monitor configuration, log/metric/trace integration, GCP telemetry, and reusable implementation examples for service and infrastructure health
Key Responsibilities
- Configure Datadog dashboards, monitors, log views, traces, and service health views
- Implement standard tagging, naming, and metadata patterns
- Integrate GCP Monitoring/Logging signals into Datadog where applicable
- Support runtime health, infra health, pipeline health, and dashboarding workstreams
- Partner with Senior SRE on alerting, SLO, and runbook standards
- Support LLM performance and cost/right-sizing dashboards where platform telemetry is needed
- Document implementation patterns for long-term owning teams
Skill Requirements
- Lead: Datadog implementation, dashboards, monitors
- Strong: OpenTelemetry/logs/metrics/traces, GCP Monitoring/Logging, GCP, service health dashboards
Working Knowledge: GKE/Cloud Run, SQL, Python, Bash, BigQuery, Databricks, AI/ML telemetry concepts
Other Requirements
- Lead: Datadog implementation, dashboards, monitors
- Strong: OpenTelemetry/logs/metrics/traces, GCP Monitoring/Logging, GCP, service health dashboards
Working Knowledge: GKE/Cloud Run, SQL, Python, Bash, BigQuery, Databricks, AI/ML telemetry concepts