Senior Site Reliability Engineer

⭐ Who we are Lodgify is a fast-growing scale-up company leading the vacation rental industry. Backed by $30M in funding, our platform empowers property owners and managers worldwide to efficiently manage and grow their business through technology. Headquartered in sunny Barcelona, we're now a team of 380+ people representing over 60 nationalities, united by a passion for transforming the future of short-term rentals.

⭐ How will you make an impact?

• Define meaningful SLIs, SLOs, and reliability targets for the platform.

• Collaborate with the software engineering teams to define and achieve the best practices for software observability, SLIs, SLOs and reliability.

• Strengthen production readiness by improving service ownership, observability, alerting, runbooks, scaling assumptions, rollback paths, and failure-mode preparedness.

• Improve the reliability, scalability, and performance of cloud, Kubernetes, and shared infrastructure, including how systems scale during growth, traffic spikes, and dependency failures.

• Build actionable observability using metrics, logs, traces, and golden signals, with tools such as Datadog, Prometheus, and Grafana.

• Implement operational and security best practices through guidelines, policies and automation.

• Reduce alert noise and improve signal quality so teams can detect, understand, and resolve issues quickly.

• Automate repetitive operational work using Python or other languages, turning recurring manual work into safer automation and clearer runbooks.

• Implement self-service Internal Developer Platform features via APIs and Kubernetes operators.

• Improve deployment safety, rollbackability, and release observability.

• Improve reliability of critical stateful systems such as databases, caches, queues, and streaming platforms.

• Participate in on-call, troubleshoot, and coordinate incident response, and facilitate blameless post-incident reviews that turn into concrete improvements.

• Execute disaster recovery drills and analyse cloud/platform usage to identify cost and resource-efficiency gains without compromising reliability.

⭐ What makes you a great fit?

• You have 7+ years of production experience operating Kubernetes-based platforms and cloud infrastructure.

• You understand and apply SRE practices: SLIs, SLOs, error budgets, production readiness, incident response, post-incident learning, toil reduction, scalability, capacity planning, high availability, backups, and disaster recovery.

• You can design and improve observability and alerting for critical systems using metrics, logs, traces, and golden signals, and are comfortable troubleshooting complex distributed systems to identify systemic reliability improvements.

• You can write maintainable software to automate operational tasks and reduce manual intervention.

• You have experience with stateful production systems such as relational databases, caches, queues, or streaming platforms.

• You know how to balance reliability, performance, cost, and delivery speed pragmatically.

• You are comfortable working in a transitional environment where SRE practices are being introduced while critical infrastructure and delivery systems still need hands-on reliability support.

• You collaborate effectively with Engineering, Platform, Security, and Product stakeholders.

• You communicate clearly, document well, and enjoy coaching teams toward stronger production ownership.

• You model initiative and accountability, raising risks early and driving improvements through to completion.

⭐ What does success look like?

• Critical services have clear owners, meaningful SLIs/SLOs, actionable alerts, dashboards, runbooks, and production readiness coverage.

• Reliability targets are consistently met across critical infrastructure and services.

• Operational toil and manual intervention are measurably reduced through automation and safer workflows.

• MTTR improves through reduced alert noise, better signal quality, stronger observability, and clear incident response playbooks and escalation paths.

• Post-incident actions are tracked, completed, and used to reduce repeat incidents.

• Disaster recovery exercises validate that critical services and infrastructure can recover within agreed expectations.

• Cloud and infrastructure resources are optimised without sacrificing performance, elasticity, or resilience.