Cloud Data Engineer

2 weeks ago

Imus, Calabarzon, Philippines beBeeCloud Full time ₱900,000 - ₱1,200,000

Exciting Career Opportunity: Cloud Data Platform Engineer

About the Role

We are seeking a skilled Cloud Data Platform Engineer to join our team. This role offers the opportunity to shape the future of cloud-native data platforms from the ground up, working alongside top experts in cloud and data.

This is a challenging and rewarding position that requires strong technical skills, excellent problem-solving abilities, and a passion for innovation.

Main Responsibilities
  • Product Development & Research: 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:
Operations & Managed Services for Customers
  • 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:
Key Requirements
  • 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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