- Veepee
- Paris, IDF
- Full-Time
- 6 days ago
Site Reliability Engineer- Data Platform (W/M/X).
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Site Reliability Engineer- Data Platform (W/M/X): our view in 3 lines...
- The Role:This role is for an engineer who keeps a large self-hosted data platform on Kubernetes reliable, fast, and cost-efficient for many internal data teams.
- The Person:The person will improve reliability of the Kubernetes data platform, define SLOs and alerting, automate infrastructure and CI/CD, handle on-call incidents with blameless postmortems, and support data teams on production readiness.
- Requirements:The ideal candidate has run Kubernetes clusters in production, uses Terraform and ArgoCD, works with Prometheus and Grafana, handles on-call and incident management, codes in Go or Python, and uses GitLab CI.
About the role
ABOUT THE TEAM
The Data Platform team builds and runs the platform behind Veepee's data: streaming, query engine, data catalog, storage and Kubernetes. It serves every data team, from BI and analytics to data science, pricing and personalisation.
We are in the middle of our move from GCP to a self-hosted, open-source data platform built on Kafka, Trino, Apache Iceberg, Apache Polaris, Ceph and Kubernetes. Projects like this are rare. You'll help build it, make it production-grade and keep it reliable.
We also work AI-first. We use Claude and GitHub Copilot every day, expose our platform to AI agents through MCP servers, and keep an AI-ready knowledge base.
TASK
- Run and improve the reliability of our data platform on Kubernetes: availability, performance, capacity, cost.
- Define and track SLOs, and improve monitoring and alerting (Prometheus, Grafana) so that fewer, more useful alerts reach people.
- Automate everything you can: infrastructure as code (Terraform, Crossplane), GitOps (ArgoCD), and CI/CD (GitLab).
- Take part in on-call [rotation details], lead incidents and write blameless postmortems that lead to lasting fixes.
- Work with data engineers and other data teams on production readiness, migrations and tooling.
- Try out AI in operations: agents that investigate incidents, MCP tools, automated runbooks.
MUST HAVE SKILLS
- Kubernetes in production: you have run clusters and the workloads on them, not only deployed to them.
- Infrastructure as code and GitOps: Terraform, plus ArgoCD or a similar tool.
- Observability: Prometheus and Grafana, SLOs, and alerting that people actually act on.
- On-call and incident management: real incidents handled, root causes found, postmortems written.
- Coding: Go or Python for automation and tooling, plus solid Linux and networking basics.
- CI/CD: GitLab CI or similar.
- Curiosity about AI: you already use AI assistants (Claude, GitHub Copilot or similar) in your daily work, and you want to find out how they can change the way we run platforms.
- Professional English, written and spoken.
NICE TO HAVE SKILLS
- Kafka (KRaft, Kafka Connect)
- Trino, Opensource : Apache Iceberg, Apache Polaris
- Object storage (Ceph, S3) and Postgres (Patroni)
- Crossplane, OPA
- GCP
- FinOps practices
- English
BENEFITS
Profit-sharing and incentive schemes
Remote work possible for up to 2 days per week
Online language-learning platform
Works Council (CSE) with a wide range of benefits
CESU vouchers (service vouchers) and holiday vouchers
Access to corporate dining facilities and smart fridges (Foodles, Kumo, Bolk)
Access to an on-site gym
️ RECRUITMENT PROCESS
-
30-minute HR Screen with a Talent Acquisition Partner
-
Interview with the Hiring Manager
- Business & Technical Interview with local Team