Big Data Energy required specialized Cloud Architecture and Big Data Optimization expertise to address rapidly escalating cloud costs associated with their data processing operations. Blue People's primary objective was to serve as Cloud FinOps and Data Engineers, focusing on redesigning the data storage and querying logic to achieve immediate, quantifiable cost reductions. The main challenge stemmed from the application's reliance on high-volume data queries and a foundational architecture that was not yet optimized for current scale within Google Cloud BigQuery. This necessitated a strategic approach that optimized table structure (using partitioning and clustering) and shifted heavy computational logic to a serverless environment (Google Cloud Function) to ensure both scalability and cost-efficiency.