Senior Site Reliability Engineer / SRE

📋 Job Overview

At a glance: Location & work model: Berlin, hybrid. Tech stack: Kubernetes on our own servers, Harvester (KubeVirt), Argo CD/Flux, Prometheus/Grafana, Longhorn/Ceph. Team: A growing SRE team – you report to our CTPO for now and to the Team Lead SRE we're hiring next; two system administrators in Pforzheim run the physical hardware. Process: Intro call · take-home task (~2h) · 90-min tech interview with our developers · leadership conversation · meet the team. Languages: Fluent English required; German is a plus, not a must.

🏢 About Fact-Finder

Most SRE jobs today mean clicking around a managed cloud console. This one doesn't. We run our own hardware in Frankfurt and are building a modern private cloud platform on Kubernetes and Harvester – on-prem by default, with elastic burst into the public cloud and the option to go cloud-only later. You won't inherit a finished SRE practice: you'll help define it, side by side with our Berlin development teams – and you won't do it alone, a Team Lead SRE hire is coming next. SRE here is an enabling discipline: you build what our developers need to ship reliably, while two system administrators in Pforzheim run the physical hardware. And the impact is direct – our product discovery technology powers more than 2,000 European online shops (Intersport, SPAR, Douglas and more), handling billions of shopper queries a year. When product discovery is slow or down, our customers lose revenue in real time.

🎯 The Role

You get to know both products, join the on-call rotation with a buddy, and own your first reliability topic – SLOs for one product, alerting that actually helps at 3 a.m., or automating away a piece of toil. By day 90 you've shipped visible improvements and know where you want to take the platform next.

✅ Key Responsibilities

• Define and own SLOs, SLIs and error budgets; drive data-informed reliability decisions
• Lead incident response end-to-end: fast detection, clear communication, blameless postmortems – and reduce whole classes of incidents structurally, not case by case
• Eliminate toil through automation and GitOps; evolve our observability (metrics, logs, traces, alerting, runbooks) across two different stacks
• Help build our custom Kubernetes operator (CRDs) that makes stateful search clusters declarative, self-healing and safely upgradable – and roll out the auto-scaling (HPA/VPA, KEDA, cluster auto scaler) today's architecture makes hard
• Plan capacity, performance and cost across on-premises and cloud – including the large-catalogue and peak-season loads our merchants care about – and use AI tools wherever they measurably speed up diagnosis and operations

📌 Required Qualifications

• Kubernetes in production – built, not just used: you've set up and maintained clusters on your own servers (e.g. kubeadm, RKE2, k3s) and know cluster lifecycle and upgrades – managed-only experience isn't enough for this role
• Lived SRE practice: SLOs, error budgets, incident management, on-call
• Hands-on experience with GitOps or comparable infrastructure/deployment automation – experience with Argo CD or Flux is a strong plus
• Solid observability skills – metrics, logs, traces, alerting that people trust
• A strong automation instinct – you'd rather fix a problem's cause than repeat its workaround
• A collaborative, enabling mindset – you see SRE as a service to our developers: you ask what they need, discuss trade-offs openly, and don't fall in love with your own solution

⭐ Desirable Experience

• Harvester, KubeVirt, vSphere/ESXi, OpenStack or similar virtualization/HCI platforms
• Container storage (Longhorn, Ceph) and datacenter networking (load balancing, ingress, VLAN)
• Auto-scaling (HPA, VPA, KEDA, cluster auto scaler) and capacity/cost planning
• Experience building Kubernetes operators/CRDs
• German language skills

🎁 Benefits

Impact from day one: Your work directly influences the revenue of leading eCommerce brands across Europe. Modern tech stack: Kubernetes, Harvester, GitOps, auto-scaling, and an exciting path toward the cloud – with room to build things right. AI-first mindset: We use AI as a real part of our daily work, not as a buzzword. Ownership & growth: Clear responsibility, short decision paths, and the opportunity to actively shape your role. Flexible work: Hybrid work model three office days per week with a focus on outcomes. Strong team: Experienced engineers, an open feedback culture, and an environment where reliability is treated as a real engineering discipline.

🛂 Visa & Eligibility