Senior Data Platform Engineer

An established international technology company operating a high-throughput, real-time data platform at massive global scale.

Platform and SRE Expertise:

• Strong hands-on experience in Platform Engineering, Site Reliability Engineering, DevOps, or infrastructure engineering.
• Advanced knowledge of Kubernetes in production, particularly stateful workloads, persistent storage, disruption management, and safe upgrades.
• Production experience with Infrastructure as Code and configuration management using tools like Terraform, Helm, or Kustomize.
• Practical experience with GitOps and automated delivery, ideally using ArgoCD, Flux, or comparable tooling.
• Experience owning production systems, participating in on-call rotations, and resolving complex incidents.

Data Platform Experience:

• Hands-on experience operating Kafka, Redpanda, or another production event-streaming platform.
• Experience administering or supporting data technologies such as Spark, Airflow, PostgreSQL, Elasticsearch, Hadoop, or Apache Druid.
• Good understanding of data ingestion, streaming, partitioning, replication, consumer lag, capacity, and performance.
• Experience implementing monitoring, alerting, dashboards, and structured root-cause analysis.
• Willingness to learn Apache Druid, Spark, Redpanda, and OpenStack if not already known.

Collaboration and Mindset:

• Strong ownership mindset and ability to operate independently in a small, high-impact team.
• Confidence contributing to architectural discussions and challenging existing solutions.
• Openness to learning unfamiliar technologies and using AI-assisted development tools.
• Clear written and spoken English.

Platform Ownership:

• Own the operational health and ongoing development of a self-hosted data platform running on Kubernetes and OpenStack.
• Operate production systems including Apache Druid, Redpanda, Spark, Airflow, PostgreSQL, and Elasticsearch.
• Participate in platform stabilization, upgrades, capacity planning, and ongoing performance improvements as the platform scales.
• Build reliable operating patterns for stateful Kubernetes workloads, including storage, replication, disruption management, and rolling upgrades.

Reliability and Incident Management:

• Define and monitor KPIs, alerts, dashboards, SLOs, and error budgets to maintain platform reliability.
• Build observability coverage using Prometheus, Grafana, logging, and distributed tracing.
• Participate in on-call rotation, respond to production incidents, and coordinate resolution of major platform issues.
• Drive root-cause analysis, post-incident reviews, runbooks, and preventive improvements.

Infrastructure and Automation:

• Codify infrastructure and platform configuration using Terraform, Helm or Kustomize, and GitOps practices.
• Improve CI/CD processes to make platform changes safe, repeatable, and easy to support.
• Automate recurring operational work and reduce manual intervention.
• Apply security, secrets management, backup, and disaster-recovery practices.

Architecture and Collaboration:

• Contribute to architectural discussions and help shape the future technology stack.
• Partner with globally distributed architects, SREs, data engineers, analysts, and data scientists.
• Translate platform requirements into scalable and supportable technical solutions.
• Use AI-assisted engineering tools pragmatically with strong quality controls for production infrastructure.

Remote work allowed within Poland; working model includes 2 days per week in Krakow office.