Team Lead - Site Reliability Engineering (all genders)

About the role

FACT-Finder is looking for a Team Lead to own the reliability, scalability and cost of its on‑premise and cloud hosting environments. You will drive the migration to a Kubernetes‑based platform on Harvester and lead a four‑person hosting team.

Key responsibilities

• Maintain operational health of hosting across Frankfurt and Stockholm data‑centers and cloud, covering availability, performance and incident management.
• Design and implement the Kubernetes‑on‑Harvester platform, including cluster topology, storage (Longhorn), networking (VLAN, load balancing, ingress), backup and disaster‑recovery.
• Build production‑grade K8s platform features: lifecycle management, upgrades, RBAC, secrets, GitOps (Argo CD / Flux), observability and policy guardrails.
• Develop and operate the NG Search Operator and auto‑scaling solutions (HPA, VPA, KEDA, cluster autoscaler).
• Define the hybrid on‑prem/cloud model, manage workload placement, burst capacity, latency and cost while keeping the architecture portable.
• Own capacity planning, cost management and turn cost into a controlled lever.
• Lead, mentor and grow the hosting team, set technical direction and foster a culture of ownership.
• Integrate AI tools into daily operations for diagnosis, automation, monitoring and insight.

Required profile

• Strong background in infrastructure or platform engineering across on‑premise and cloud environments.
• Proven people‑leadership experience with excellent communication and stakeholder‑management skills.
• Hands‑on experience migrating bare‑metal or classic VMs to a Kubernetes‑based platform, including stateful workloads and storage migration.
• Fluent English; German is a plus.

Required skills

• Kubernetes (cluster lifecycle, upgrades, networking, storage, RBAC, observability)
• Harvester or comparable HCI/virtualisation platforms (e.g., KubeVirt, vSphere/ESXi, OpenStack)
• GitOps tools – Argo CD, Flux
• Longhorn storage
• VLAN, load balancing, ingress controllers
• Custom Kubernetes operators / CRDs
• Auto‑scaling primitives – HPA, VPA, KEDA, cluster autoscaler
• Capacity planning and cost management for hybrid on‑prem/cloud setups
• AI‑assisted operational tools