
Cloud Native Data Platform Engineer
17 hours ago
Job Opportunity:
This is a unique chance to shape the future of cloud-native data platforms from the ground up, working alongside top experts in the field.
About Cloud-Native Data PlatformsCloud-Native Data Platforms aim at leading the industry by focusing on building a firm technological foundation and developing diversified ecosystem products.
They provide customized solutions to meet specific needs, consolidate technology and diverse business solutions in one platform, and deliver the future by helping customers achieve business outcomes faster.
- Customized solutions
- All-in-one platform
- Local market leadership
- Deliver the future
- Collaborate with the team to design technical architecture for Cloud Data Platform services (Data Ingestion, Processing, Storage, Query, Visualization, Security, Governance).
- Implement and integrate Data Platform components: Kafka, NiFi, Airflow, Spark, Flink, Iceberg, Trino, Superset, dbt…
- Build and operate CI/CD systems and Infrastructure as Code (Terraform, Helm, ArgoCD…).
- Research and propose new technologies to optimize performance and enhance the product.
- Support deployment, configuration, and optimization of Cloud Data Platform for customers.
- Monitor, troubleshoot incidents, and ensure service SLA compliance.
- Operate monitoring, alerting, and logging systems (Prometheus, Grafana, ELK, Loki…).
- Support troubleshooting of data pipelines, data source connections, and security incidents.
- Participate in training and guiding customers on platform usage.
Must-have
- 3–5 years of experience in DataOps, DevOps, Platform Engineer, or Data Engineer roles.
- Proficiency in Kubernetes, Docker, and microservices architecture.
- Hands-on experience deploying or operating at least some Data Platform services (e.g., Kafka, Airflow, Spark).
- Strong scripting skills (Python or Bash).
- Experience with CI/CD and GitOps (GitLab CI, Jenkins, or ArgoCD).
- Basic understanding of Data Pipelines and Data Engineering concepts.
Nice-to-have
- Experience in designing or operating Data Lakehouse / Data Warehouse.
- Experience providing Managed Services for enterprise customers.
- Knowledge of data security (IAM, RBAC, TLS, Network Policy, etc.).
- Relevant certifications in Kubernetes (CKA, CKAD) or Cloud (AWS, GCP, Azure).
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