Mexico Biomass Analytics: End-to-End Data Pipeline

This project solves a critical data logistics problem in Mexico's renewable energy sector. It combines fragmented agricultural waste data (SIAP) and existing infrastructure records (SEMARNAT) to identify the national biomass "Opportunity Gap." Designed with an EtLT architecture, the pipeline uses Terraform for IaC deployment on Google Cloud Platform. Bruin serves as the unified orchestrator handling data ingestion via Python, and heavy business transformations using SQL natively in BigQuery. The optimized data warehouse powers an interactive Looker Studio dashboard and integrates with Bruin Cloud's AI Data Analyst to provide actionable, natural-language insights for infrastructure investment. Tech Stack: Bruin, GCP (Cloud Storage, BigQuery), Terraform, Python, SQL, Looker Studio.