Core Responsibilities

• Pipeline Orchestration: Develop, test, and maintain Airflow DAGs in Cloud Composer. This includes managing task dependencies, implementing custom operators, and monitoring production workflows.
• Data Modeling & Architecture: Implement schema designs and table structures in BigQuery. You will be responsible for creating ERDs, optimizing query performance through partitioning/clustering, and managing Dataform scripts for SQL transformations.
• Python Development: Write modular Python for custom API integrations, data processing tasks, and internal engineering tools.
• Team Collaboration: Work within the existing engineering framework to support project-specific data requirements, following established Git-based CI/CD workflows and documentation standards.
• Performance Optimization: Assist in the audit and optimization of BigQuery resources to manage processing costs and improve execution speeds.

Technical Requirements

• GCP Experience: Professional experience working within the Google Cloud Platform ecosystem.
• Cloud Composer / Apache Airflow: Proven experience building and troubleshooting complex orchestration workflows.
• Python: Proficiency in Python for data engineering and systems integration.
• SQL & BigQuery: Expert-level SQL skills and experience with structured data modeling, including schema design and ERDs.
• Version Control: Experience using Git/GitHub for collaborative development and CI/CD.

Preferred Qualifications

• Certification: GCP Professional Data Engineer (PDE).
• Domain Experience: Experience modelling data for marketing and/or tourism performance/attribution.
• AI Exposure: Exposure building LLM agents or data retrieval layers for LLM agents  (RAG, Embeddings, MCP)
• Tooling: Hands-on experience with Dataform or dbt for version-controlled SQL modeling.