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Open nowFirst seen 32 hours ago

Google Cloud Data Engineer

PM Consulting1,469 open roles

Where
Taguig, Metro Manila, Philippines
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Your applicationOpen nowGoogle Cloud Data EngineerPM Consulting · Taguig, Metro Manila, Philippines

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. PM Consulting postings stay open a median of 1 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: first seen 32 hours ago

PM Consulting median: 1 days open

The posting

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.
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