
Developed end-to-end data capabilities for climate and economic analytics within the Prof-Drake-UMD/INST767-Sp25 repository, focusing on reliable data ingestion, transformation, and analysis. Built a pipeline using Python and Airflow to orchestrate data flows from weather, air quality, and World Bank APIs, transforming and categorizing the data before loading it into BigQuery. Enhanced analytics by optimizing SQL queries to identify top cities by GDP growth with clean air, supporting clearer business insights. Improved repository structure through asset organization and code cleanup, which streamlined onboarding and maintainability. Leveraged skills in API integration, ETL, and cloud computing to deliver robust solutions.
Month 2025-05: Delivered end-to-end data capabilities for climate and economic analytics, improved top-city insights, and cleaned repository structure to boost maintainability and onboarding. Business impact centers on faster, more reliable analytics and clearer data signals for decision-making.
Month 2025-05: Delivered end-to-end data capabilities for climate and economic analytics, improved top-city insights, and cleaned repository structure to boost maintainability and onboarding. Business impact centers on faster, more reliable analytics and clearer data signals for decision-making.

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