Google Cloud Data Engineer - Scalable Pipelines & Real Time

Create Synergies Inc.; Taguig; On-site; PHP 1,339,200 - 2,008,800; Full time

Job summary

Create Synergies Inc. seeks an experienced Data Engineer to design, build, and maintain scalable data platforms in Google Cloud.

The role focuses on reliable, secure data solutions for analytics, reporting, and data-driven initiatives across the organization. The ideal candidate has 5–8 years in data or cloud engineering, with hands-on Google Cloud experience and familiarity with enterprise-scale data ecosystems.

Qualifications

• 5–8 years of experience in Data Engineering or Cloud Engineering.
• Proven end-to-end data solutions in Google Cloud Platform.
• Experience with enterprise-scale data platforms and complex ecosystems.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Google Cloud technologies.
• Build and optimize data models and warehouse structures for large-scale analytics.
• Implement and support batch and real-time data ingestion frameworks.
• Apply DataOps practices to improve data quality, monitoring, testing, and operations.
• Develop and maintain CI/CD processes for data platform deployments.
• Automate infrastructure provisioning and management using IaC (Terraform).
• Monitor, troubleshoot, and optimize production data environments for performance and reliability.
• Collaborate with engineering, analytics, and business teams to deliver data solutions.
• Ensure adherence to security, governance, and data protection standards.

Skills

Data Engineering

Google Cloud

CI/CD

DataOps

IaC

Docker

Kubernetes

Git

Tools

Terraform

Job description

Create Synergies Inc. seeks an experienced Data Engineer to design, build, and maintain scalable data platforms in Google Cloud.

The role focuses on reliable, secure data solutions for analytics, reporting, and data-driven initiatives across the organization. The ideal candidate has 5–8 years in data or cloud engineering, with hands-on Google Cloud experience and familiarity with enterprise-scale data ecosystems.