About this Position
Henkel is looking for an Observability Engineer to join our Platform Engineering team. In this role, you will help design, build, and continuously improve the observability foundation that gives our engineering teams deep visibility into the health and performance of our systems running on Google Cloud Platform, Microsoft Azure, and OpenShift. You will work closely with platform engineering, cloud architecture and application teams to make sure the right signals — metrics, logs, and traces — are collected, visualized, and alerted on, so issues are caught before they impact users.
What you´ll do
- Design, build, and maintain observability pipelines across our multi-cloud environment (Azure, GCP), covering metrics, logs, and traces.
- Create and maintain dashboards that give engineering teams clear, actionable visibility into system health, performance, and business-relevant metrics.
- Integrate metrics collection across services and infrastructure, ensuring consistent instrumentation standards.
- Build and continuously improve alerting frameworks used to support on-call rotations, balancing signal quality with alert fatigue.
- Work with industry-standard observability tools such as Grafana, Prometheus, and the ELK Stack to collect, store, and visualize telemetry data.
- Operate and optimize APM tooling (e.g., Dynatrace, Datadog) to support application performance monitoring and root-cause analysis.
- Leverage Azure Monitor and Kusto Query Language (KQL) to build queries, alerts, and workbooks for Azure-hosted workloads.
- Leverage GCP Monitoring (formerly Stackdriver) for log and metrics aggregation across GCP-hosted services.
- Work on the Site Reliability Engineering practice focusing on co-defining SLOs and OLAs to translate collected metric points into business KPIs and subsequent dashboards
- Partner with platform, DevOps, and application engineering teams to define what "good observability" looks like for each service and help teams adopt it.
- Contribute to incident response and postmortem processes by improving the observability signals that support faster detection and diagnosis.
- Document observability standards, runbooks, and best practices to help scale knowledge across the engineering organization.
- Actively participate in the Community of Practice / Cloud guild to foster cross-domain knowledge sharing and reduce knowledge silos
