GCP Engineer

Industry & Sector:

About The Opportunity

• Design, implement, and maintain scalable data pipelines using GCP services (BigQuery, Dataflow, Cloud Composer, Dataform, Pub/Sub).
• Develop Python-based data processing jobs, API endpoints, and automation scripts for ingestion, transformation, and orchestration.
• Build and optimize ETL/ELT processes for batch and streaming workloads, ensuring data quality, throughput, and low latency.
• Implement CI/CD pipelines, IaC, and deployment automation to enable repeatable, secure releases (Git, Terraform, container tools).
• Monitor, troubleshoot, and tune systems for performance, reliability, observability, and cost efficiency on GCP.
• Collaborate with data scientists, product managers, and platform teams to align architecture, data models, and integration patterns.
  

Skills & Qualifications

Must-Have

• 3+ years hands-on experience with Google Cloud Platform services—BigQuery, Dataflow, Cloud Composer (Airflow), Pub/Sub, and Dataform.
• Strong Python skills for data engineering, automation, and API development.
• Proven experience building ETL/ELT pipelines for batch and streaming data; solid understanding of data modelling and schema design.
• Experience with CI/CD, Git workflows, and Infrastructure as Code (Terraform) for cloud deployments.
• Familiarity with containerisation and orchestration (Docker, Kubernetes/GKE) and production deployment patterns.
• Operational skills in monitoring, logging, troubleshooting, and cost optimisation on GCP (Cloud Monitoring / Logging).
  

Preferred

• Experience with API design (REST/gRPC) and integrating data platforms with microservices.
• Knowledge of observability stacks (Prometheus, Grafana) and advanced query/optimization techniques in BigQuery.
• Exposure to search platforms (ElasticSearch) or data cataloging/metadata tools.
• Certifications: Google Cloud Professional Data Engineer or Professional Cloud Engineer.
  

• Collaborative, product-focused engineering culture with strong emphasis on ownership and continuous improvement.
• Opportunities for technical growth—mentoring, certifications, and working across analytics, ML, and platform projects.
• Competitive compensation, flexible hybrid work options, and support for professional development.