Requirements

Expected technologies

Google Cloud Platform

Python

SQL

Optional technologies

Terraform

Deployment Manager

Our requirements

• 5+ years of experience in data architecture, engineering, or similar roles.
• Proven expertise in GCP data services, especially BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Dataproc.
• Strong hands-on experience with data pipeline design and orchestration (ETL/ELT).
• Proficiency with Python, SQL, and data modeling techniques.
• Knowledge of data governance, security, and compliance in a cloud environment.
• Experience with Infrastructure as Code (e.g., Terraform, Deployment Manager).
• Familiarity with CI/CD practices in a data engineering context.
• Practical understanding of integrating ML models into data solutions using GCP tools.
• Strong communication and stakeholder management skills.
• Certification in GCP Data Engineering or Cloud Architecture is mandatory.
• Language skills: Fluent in English.

Your responsibilities

• Design end-to-end data architecture solutions leveraging GCP-native services (e.g., BigQuery, Cloud Storage, Dataflow, Pub/Sub, Dataproc).
• Define data strategies supporting batch and real-time processing, scalable storage, and high-availability.
• Collaborate with stakeholders to understand business objectives and translate them into scalable and secure data solutions.
• Develop and maintain ELT/ETL pipelines using Cloud Composer, Apache Beam, and other GCP tools.
• Ensure compliance with data governance policies, including security, access management (IAM), and regulatory standards (e.g., DLP, VPC-SC).
• Integrate ML capabilities into data pipelines using Vertex AI, AutoML, or TensorFlow on GCP.
• Implement Infrastructure as Code (IaC) using tools like Terraform or Deployment Manager.
• Establish CI/CD practices for data pipelines using Cloud Build and GitOps workflows.
• Contribute to architectural reviews, documentation, and internal best practices.