Google Data Engineer

apartmentHRTx Inc placeManila calendar_month 
Hybrid (3x a week RTO) | BGC, Taguig
  • Applicant must be open to any shift.
Key Responsibilities
  • Data Pipeline Development: Design and build batch and streaming ETL/ELT pipelines using BigQuery, Dataflow, Cloud Composer, and Pub/Sub.
  • Data Modeling & Optimization: Architect BigQuery data models optimized for high performance and cost efficiency.
  • Automation & DevOps: Implement CI/CD, Infrastructure as Code (Terraform), and DataOps for automated testing, monitoring, and deployments.
  • Operations & Reliability: Monitor, troubleshoot, and optimize production data systems to maintain performance.
  • Cross-Functional Collaboration: Partner with data scientists, analysts, and software engineers to deliver data solutions.
  • Security & Governance: Maintain compliance with enterprise security, cloud governance, and data protection standards.
  • Containerization: Support containerized workloads and orchestration using Docker and Kubernetes.
  • System Architecture: Drive continuous improvements across data architecture and GCP capabilities.
Qualifications
  • Education: Bachelor's Degree holder.
  • Experience: 5–8+ years in data or cloud engineering, with a track record of delivering end-to-end data solutions on enterprise-scale GCP environments.
  • GCP Data Stack: Strong hands-on expertise with BigQuery, Dataflow, Pub/Sub, and Cloud Composer.
  • Engineering & Automation: Proficiency in Git, CI/CD for data workflows, Infrastructure as Code (Terraform), and containerization/orchestration (Docker, Kubernetes).
  • Cloud Infrastructure: Solid grasp of cloud networking (VPCs, subnets, firewalls, load balancing) and cloud security best practices.
  • Data Practices: Expertise in DataOps frameworks, automated data quality validation, and designing high-volume data pipelines.
Preferred Qualifications
  • Certifications: GCP Professional Data Engineer, Cloud Architect, Cloud DevOps Engineer, or Cloud Developer.
  • Domain Experience: Prior exposure working within regulated or highly governed data environments.
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