Description

You will build and maintain machine learning pipelines and data workflows on Google Cloud Platform.

Responsibilities

• Develop and manage data pipelines using Cloud Composer, Airflow, and DBT.
• Design and implement data models and system architectures.
• Maintain high code quality through unit testing, end-to-end testing, and rigorous code reviews.
• Build and manage CI/CD pipelines using GitHub Actions or Azure DevOps.
• Manage infrastructure and access control using IAM, service accounts, and Infrastructure as Code.

Required Skills

• 5+ years of professional experience in machine learning or data engineering roles.
• Deep knowledge of Python programming, including OOP and best practices (flake8, mypy, black, SonarQube).
• Expertise in SQL and BigQuery.
• Strong experience with DBT, preferably within GCP environments.
• Deep understanding of Docker and containerization.
• Proficiency with Git, including pull requests and merge conflict resolution.
• Experience with Unix systems, shell scripting, and Docker installations.
• Advanced testing skills using Pytest, fixtures, and unittest.
• Knowledge of Data Catalog and cloud diagnostic skills.

Preferred Skills

• Experience with Dataflow, Kubernetes (K8s), Vertex AI pipelines, or Kubeflow pipelines.

Key Skills

Education

Any Graduate