Data Platform Engineer · Seoul, Korea
I run Spark and StarRocks as a service on Kubernetes, and I came to it from the infrastructure side:
CI/CD, IaC and monitoring first, then the data pipelines, then the query engines themselves.
Currently at SK Telecom, on a multi-tenant data platform.
- Query engines as a self-service platform. Per-user Spark and StarRocks clusters on Kubernetes: a Java and Spring Boot orchestration service for the cluster lifecycle, plus custom operators.
- Engine tuning. FE and CN memory, data cache, CPU, query queue, and Iceberg external catalog behavior.
- Observability. Metric sidecars per cluster, rule-based diagnostics, Grafana dashboards.
- Pipelines. Kafka streaming and orchestrated batch jobs.
- Cloud-native infrastructure. Kubernetes, Terraform, ArgoCD and GitOps, CI/CD, LGTM stack monitoring.
| Query & data | |
| Platform | |
| Backend | |
| Observability |
CKA (2022.12), CKAD (2025.07), KCNA (2025.07), KCSA · The Linux Foundation
NCP Certified Professional (2021.12) · Naver Cloud Platform
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