Staff SRE: Cloud Databases Reliability & Scale

Grafana Labs

Ireland

On-site

EUR 130,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Remote work
Learning stipend
Headspace subscription
Employee assistance program
Parental leave

Job summary

Grafana Labs is seeking a Staff Software Engineer - SRE to boost reliability for Grafana Cloud databases across AWS, GCP, and Azure. You will own production reliability for high‑SLA customers, design scalable automation, and drive incident response from detection to post‑mortem.

You will collaborate with embedded product squads, influence architecture, and define per‑tenant SLOs to sustain rapid growth while reducing toil and improving observability.

Qualifications

  • 8+ years of engineering experience, 4+ years in SRE/production engineering.
  • Strong programming experience in Go, Python or Java.
  • Kubernetes expertise in AWS, GCP or Azure.
  • Experience with incident response and post-incident reviews.
  • Comfortable working autonomously within product engineering teams.
  • Ability to design scalable, fault-tolerant systems and SLOs.

Responsibilities

  • Own production reliability for high-SLA Grafana Cloud databases.
  • Design automation to scale reliability practices and reduce toil.
  • Lead incident response, PIRs, and customer communications.
  • Partner with product engineering squads to influence design and roadmaps.
  • Define and evolve per-tenant SLOs and reliability models.
  • Improve observability and alert quality across multi-tenant environments.

Skills

Go
Python
Java
Kubernetes
Linux
Networking
SRE/CRE
Incident Response
Autonomy

Tools

Helm
Terraform
Jsonnet

Job description

Grafana Labs is seeking a Staff Software Engineer - SRE to boost reliability for Grafana Cloud databases across AWS, GCP, and Azure. You will own production reliability for high‑SLA customers, design scalable automation, and drive incident response from detection to post‑mortem.

You will collaborate with embedded product squads, influence architecture, and define per‑tenant SLOs to sustain rapid growth while reducing toil and improving observability.

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