GCP Data Engineer – Distributed Cloud

About the role

We are seeking an experienced GCP Data Engineer to design, build and optimise robust, scalable and highly‑available data pipelines and ETL/ELT solutions on Google Cloud Platform. The role focuses on leveraging native GCP services to ensure data quality, automation and performance across the data lifecycle.

Key responsibilities

• Design, build and maintain scalable data pipelines and ETL/ELT processes using Cloud Dataflow (Apache Beam), Cloud Dataproc and BigQuery.
• Develop and optimise data ingestion workflows with Cloud Pub/Sub and Cloud Storage.
• Implement data quality checks, monitoring and validation across GCP systems.
• Collaborate with Data Scientists and Analysts to prepare data for reporting, analytics and Machine‑Learning (e.g., Vertex AI).
• Automate deployment, monitoring and testing of data infrastructure using Terraform and CI/CD practices.
• Manage and optimise BigQuery and Cloud Storage for performance and cost efficiency.
• Provide technical guidance on data architecture and technology choices within GCP.

Required profile

• 3+ years of proven experience as a Data Engineer building production‑grade pipelines.
• Hands‑on expertise with GCP data services including BigQuery, Cloud Dataflow, Cloud Storage and Cloud Pub/Sub.
• Strong proficiency in SQL and data‑warehousing concepts.
• Experience with a programming language for data engineering, preferably Python.
• Familiarity with Infrastructure as Code tools such as Terraform.

Required skills

• Google Cloud Platform (BigQuery, Cloud Dataflow, Cloud Dataproc, Cloud Pub/Sub, Cloud Storage).
• SQL and data modelling.
• Python programming.
• Terraform for IaC.
• CI/CD pipelines.
• Understanding of distributed systems and ETL/ELT frameworks.