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?
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Define meaningful SLIs, SLOs, and reliability targets for the platform.
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Collaborate with the software engineering teams to define and achieve the best practices for software observability, SLIs, SLOs and reliability.
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Strengthen production readiness by improving service ownership, observability, alerting, runbooks, scaling assumptions, rollback paths, and failure-mode preparedness.
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Improve the reliability, scalability, and performance of cloud, Kubernetes, and shared infrastructure, including how systems scale during growth, traffic spikes, and dependency failures.
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Build actionable observability using metrics, logs, traces, and golden signals, with tools such as Datadog, Prometheus, and Grafana.
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Implement operational and security best practices through guidelines, policies and automation.
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Reduce alert noise and improve signal quality so teams can detect, understand, and resolve issues quickly.
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Automate repetitive operational work using Python or other languages, turning recurring manual work into safer automation and clearer runbooks.
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Implement self-service Internal Developer Platform features via APIs and Kubernetes operators.
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Improve deployment safety, rollbackability, and release observability.
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Improve reliability of critical stateful systems such as databases, caches, queues, and streaming platforms.
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Participate in on-call, troubleshoot, and coordinate incident response, and facilitate blameless post-incident reviews that turn into concrete improvements.
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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?
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You have 7+ years of production experience operating Kubernetes-based platforms and cloud infrastructure.
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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.
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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.
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You can write maintainable software to automate operational tasks and reduce manual intervention.
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You have experience with stateful production systems such as relational databases, caches, queues, or streaming platforms.
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You know how to balance reliability, performance, cost, and delivery speed pragmatically.
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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.
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You collaborate effectively with Engineering, Platform, Security, and Product stakeholders.
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You communicate clearly, document well, and enjoy coaching teams toward stronger production ownership.
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You model initiative and accountability, raising risks early and driving improvements through to completion.
⭐ What does success look like?
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Critical services have clear owners, meaningful SLIs/SLOs, actionable alerts, dashboards, runbooks, and production readiness coverage.
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Reliability targets are consistently met across critical infrastructure and services.
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Operational toil and manual intervention are measurably reduced through automation and safer workflows.
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MTTR improves through reduced alert noise, better signal quality, stronger observability, and clear incident response playbooks and escalation paths.
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Post-incident actions are tracked, completed, and used to reduce repeat incidents.
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Disaster recovery exercises validate that critical services and infrastructure can recover within agreed expectations.
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Cloud and infrastructure resources are optimised without sacrificing performance, elasticity, or resilience.