Observability Engineer | Kubernetes, Prometheus, Grafana, Thanos, Loki

Role Description: Observability Engineer

Enterprise Kubernetes Platform | Financial Services

ABOUT THE ROLE

We are seeking an experienced Observability Engineer to join our Enterprise Kubernetes Platform team at a leading financial services organization. You’ll own the complete observability stack across 50+ production Kubernetes clusters, providing metrics, logging, tracing, and alerting capabilities that ensure exceptional reliability and performance for mission-critical applications.

This role combines deep technical expertise in modern observability tools with emerging AI/ML capabilities to build intelligent monitoring solutions, predictive alerting, and self-healing infrastructure.

WHAT YOU’LL DO

OBSERVABILITY STACK OWNERSHIP

Design, deploy, and maintain enterprise-scale observability infrastructure including Prometheus, Grafana, Thanos, Loki, and modern collection agents.
Manage observability deployments using GitOps principles and infrastructure as code.
Implement long-term metrics storage solutions with cloud object storage.
Maintain and upgrade observability components across development, QA, UAT, production, and DR environments.
Configure distributed observability architecture spanning multiple datacenters and cloud providers.

METRICS & MONITORING

Design and implement Prometheus monitoring strategies for Kubernetes infrastructure and containerized applications.
Create ServiceMonitors, PodMonitors for automated metrics collection.
Develop rules for intelligent alerting with minimal false positives.
Configure multi-cluster metrics federation and aggregation.
Optimize metrics cardinality, storage efficiency, and query performance.
Implement recording rules for pre-aggregated metrics and SLI calculations.

DASHBOARDS & VISUALIZATION

Build comprehensive Grafana dashboards for infrastructure health, application performance, and business metrics.
Create reusable dashboard

Competências necessárias

PrometheusGrafanaThanosLokiKubernetes observabilityGitOpsInfrastructure as CodeLong-term metrics storage with cloud object storageMulti-cluster / multi-datacenter observability architectureServiceMonitor and PodMonitor configurationAlerting strategy and rule development (intelligent alerting, reducing false positives)Metrics cardinality optimization and query performance tuningRecording rules and SLI implementationDashboard design and Grafana visualizationAI/ML-driven observability (predictive alerting, self-healing infrastructure)

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