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Mid LevelFull-timePythonRailsKubernetesElasticsearchFigmaGoAPIDevOps
Salary Range
$69,360 - $93,840 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for an experienced Observability Infrastructure Engineer to join our Platform Engineering organization at Adyen. You will be part of the team responsible for building and running Observability pillars on premise and on Kubernetes, managing systems that collect, process, and store logs, metrics, and traces for hundreds of product teams.
Key Responsibilities
- βBuild the next generation of our platform: Design and implement the future architecture of our logging and metrics systems, redesigning infrastructure to support new global regions with data isolation and regulatory compliance.
- βOwn infrastructure operations: Take full ownership of our hybrid infrastructure, managing the lifecycle of over 1,500 servers across bare-metal and Kubernetes environments.
- βAutomate to reduce toil: Write code in Go or Python to eliminate manual operational tasks, building self-healing systems and improving CI pipelines for safe, predictable, automated changes.
- βOptimize for scale and performance: Dive into performance bottlenecks within distributed tracing and logging pipelines, tuning Elasticsearch clusters, optimizing Prometheus and VictoriaMetrics storage, and ensuring OpenTelemetry implementation handles peak traffic.
- βReliability and Engineering: Participate in on-call rotations while focusing on engineering solutions that prevent alerts, upgrade our stack to latest versions, and improve self-service experience with automated guardrails and quota management.
Requirements
- β4+ years of experience in the observability domain or relevant platform/infrastructure domain.
- βObservability Stack Expertise: Hands-on experience operating core telemetry data stores at scale (Elasticsearch/Opensearch/VictoriaLogs/Clickhouse for logging, Prometheus/VictoriaMetrics for metrics, Grafana Tempo for distributed tracing).
- βLinux Experience: Understanding of the operating system at kernel level, able to debug complex networking, file system, and performance issues on bare metal and virtualized hardware.
- βProduction Kubernetes Experience: Proven hands-on experience operating and troubleshooting production workloads on Kubernetes (on-prem and/or cloud), with strong day-to-day use of kubectl and Kubernetes primitives.
- βSoftware Engineering Mindset: Proficiency in Go or Python, building tools and automation platforms that treat infrastructure as code.
- βNice to have
- βExperience with large scale, multi-tenant isolation and quota or cost governance approaches for telemetry platforms.
- βFamiliarity with regulated environments where security, audibility, and data handling requirements shape platform design decisions.
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