SRE - DataPlatform Ajouter aux favoris
- Own reliability of core data services: Trino, Iceberg, S3 / Ceph, Kafka, Kafka Connect, Schema Registry
- Define and enforce SLIs/SLOs, error budgets, and on-call runbooks - solid SRE foundations are non-negotiable
- Build full-stack observability with Prometheus and Grafana: metrics, dashboards, alerting pipelines, and anomaly detection
- Manage and harden PostgreSQL clusters via Patroni for high-availability control-plane services
- Operate and scale Kafka Connect clusters: connector lifecycle, offset management, dead-letter queues, and task rebalancing
- Maintain the Schema Registry as the single source of truth for Avro/Protobuf/JSON schemas - enforce compatibility rules and schema evolution policies
- Monitor consumer lag, connector throughput, and broker health via Prometheus JMX exporters and Grafana dashboards
- Ensure end-to-end data contract integrity between producers and Iceberg/S3 consumers
- Operate production Kubernetes clusters (GKE/EKS + on-prem) - capacity planning, upgrades, PodDisruptionBudgets, resource quotas
- Architect and manage Kube-in-Kube topologies to provide strong tenant isolation for data platform workloads - each team gets a dedicated virtual cluster without the overhead of a full physical cluster
- Automate infrastructure and resource provisioning with Crossplane: define composite resources (XRDs) so data teams can self-serve Kafka topics, Trino namespaces, and S3 buckets through Kubernetes-native APIs
- Maintain GitOps pipelines for platform deployment and configuration drift detection
- Migrate from public cloud data warehouse to VeepeeCloud Iceberg-based lakehouse - managing coexistence, schema evolution, and time-travel
- Architect resilient ingestion, transformation, and serving layers around Trino + S3
- Optimize Trino query performance: memory limits, spilling, cost-based optimizer tuning
- Build agentic self-service tooling so data teams can provision Trino/Iceberg resources and Kafka Connect pipelines autonomously via Crossplane - reducing toil and ops bottlenecks
- Develop FinOps dashboards (compute, storage, query cost) with Grafana and Prometheus-based cost exporters
- Write clear technical documentation, runbooks, and internal ADRs
- Design and implement multi-datacenter strategies across FR1 / NL1 - active-active and active-passive topologies
- Leverage Fast Erasure Coding on object storage (Ceph/S3) to maximize durability with minimal replication overhead
- Ensure data replication consistency across sites for Iceberg table metadata, Trino catalogs, and Schema Registry subjects
- Lead DRP exercises: failover playbooks, RTO/RPO validation, postmortems
- Strong experience with Kubernetes in production environments
- Experience with Kube-in-Kube technologies (vCluster or similar)
- Solid understanding of SRE principles (SLIs/SLOs, error budgets)
- Experience with Prometheus and Grafana
- Experience with Infrastructure as Code (Terraform or similar)
- Experience with Crossplane
- Familiarity with GitOps workflows
- Experience with S3 and object storage technologies
- Experience with PostgreSQL and Patroni
- Experience with Kafka, Kafka Connect, and Schema Registry
- Fluent in English
- Experience with multi-datacenter architectures (FR1/NL1)
- Experience designing disaster recovery plans and failover playbooks
- Experience with Fast Erasure Coding (Ceph/S3)
- Experience with Trino, Iceberg, and Lakehouse technologies
- Experience with Airflow
- Experience building agentic self-service platforms
- Knowledge of FinOps and cost optimization practices
- Programming experience in Python, Java, or Go
- Variable bonus
- E-learning platform (self-education courses)
- Meetups & conferences (local and international)
- Flexible office - up to 2 days remote
- International teams (France & Spain)
- 1 30-minute HR Screen with a Veepeeᵀᵉᶜʰ Recruiter
- 2 General Technical exchange
- 3 Technical exchange with the manager
- 4 Team Interview
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