Google Cloud Data Engineer
# Google Cloud Data Engineer **PM Consulting** · Philippines · `Remote` · `Full Time` 💼 **Уровень роли:** `Mid-level` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Data-Engineer]` `[Cloud-Engineer]` `[Google-Cloud-Engineer]` `[Data-Platform-Engineer]` `[ETL-Developer]` `[Google-Cloud-Data-Engineer]` `[GCP-Data-Engineer]` `[Cloud-Data-Engineer]` `[GCP-Data-Engineering]` --- ### About the Role Position Overview We are seeking an experienced Data Engineer to design, build, and maintain scalable data platforms and processing solutions within a Google Cloud environment. The role involves translating business requirements into reliable, secure, and high-performing data solutions that support analytics, reporting, and data-driven initiatives across the organization. Key Responsibilities - Design, develop, and maintain scalable ETL/ELT pipelines using Google Cloud technologies. - Build and optimize data models and warehouse structures to support large-scale analytical workloads. - Implement and support both batch and real-time data ingestion frameworks. - Apply DataOps practices to improve data quality, monitoring, testing, and operational efficiency. - Develop and maintain CI/CD processes for data platform deployments. - Automate infrastructure provisioning and management using Infrastructure as Code (IaC) methodologies. - Monitor, troubleshoot, and optimize production data environments to ensure performance, availability, and reliability. - Collaborate with cross-functional stakeholders, including engineering, analytics, and business teams, to deliver data solutions. - Ensure adherence to security, governance, compliance, and data protection standards. - Support containerized workloads and orchestration platforms where required. - Contribute to the continuous improvement of data architecture, engineering standards, and platform capabilities. Qualifications Experience - Minimum of 5–8 years of experience in Data Engineering, Cloud Engineering, or related disciplines. - Proven experience delivering end-to-end data solutions in a Google Cloud Platform environment. - Experience working with enterprise-scale data platforms and complex data ecosystems. Preferred Certifications - Professional-level Google Cloud certifications in Data Engineering, Cloud Architecture, DevOps, or Application Development are advantageous. Technical Requirements Cloud and Platform Expertise - Strong hands-on experience with Google Cloud data services, including data warehousing, data processing, orchestration, and messaging technologies. - Understanding of cloud networking concepts such as virtual networks, subnetting, load balancing, and firewall configurations. - Knowledge of cloud security principles and best practices for data environments. Engineering and Automation - Experience implementing CI/CD pipelines for data engineering solutions. - Hands-on experience with Infrastructure as Code tools, such as Terraform. - Familiarity with containerization and orchestration technologies, including Docker and Kubernetes. - Proficiency in source code management and version control practices using Git. Data Engineering Practices - Strong understanding of DataOps principles and automated data quality processes. - Experience designing and supporting high-volume, enterprise-scale data pipelines. - Exposure to regulated or highly governed environments is an advantage. Key Competencies - Strong analytical and problem-solving skills. - Ability to work effectively in cross-functional teams. - Excellent communication and stakeholder management capabilities. - Commitment to delivering scalable, reliable, and secure data solutions. Originally posted on Himalayas
- Data-Engineer
- Cloud-Engineer
- Google-Cloud-Engineer
- Data-Platform-Engineer
- ETL-Developer
- Google-Cloud-Data-Engineer
- GCP-Data-Engineer
- Cloud-Data-Engineer
- GCP-Data-Engineering
Наблюдалась 2026-10-01, впервые 2026-10-01, источник — Himalayas (JSON API).