Data Engineer with GCP

The role focuses on enhancing data-driven personalization for strategic digital products by designing and implementing scalable data architectures on Google Cloud to improve user engagement, retention, and monetization through relevant content delivery.

• Experience with Google Cloud Platform (GCP).
• Proficient in Python and FastAPI.
• Strong skills in dbt, SQL, and BigQuery.
• Familiarity with data pipeline frameworks like Airflow.
• Understanding of Kubernetes and Docker for containerization.

Nice to have:

• Experience with Vertex AI for machine learning initiatives.
• Knowledge of Terraform for infrastructure as code.
• Experience with CI/CD practices, particularly in GitLab.
• Familiarity with project tracking tools like JIRA and Confluence.

• Design and implement scalable data pipelines using Google Cloud technologies (e.g., BigQuery, Dataflow, Pub/Sub).
• Develop and optimize both batch and streaming data pipelines for personalization use cases.
• Transform and provision user and content-related data for machine learning applications.
• Implement data quality checks and establish logging and monitoring mechanisms.
• Optimize existing data processing workflows for improved performance.
• Integrate machine learning models into production workflows.
• Document data structures, transformation logic, and relevant interfaces.
• Provide technical consulting on event structures, tracking, and data architecture within the personalization framework.