Nicolás Alberto Ramírez García

Designed and deployed scalable ETL pipelines using MySQL, PostgreSQL, BigQuery, Python, and cloud services optimizing data flow and performance. Automated data processes for market operations enabling real-time insights and reducing manual workload. Implemented logistics optimization models combining BigQuery and Cloud Functions with clustering and customer segmentation to improve route efficiency and coverage. Built AI/ML-ready infrastructure consolidating data to support demand forecasting and behavioral analysis use cases.

Design, develop, and automate scalable ETL/ELT pipelines, integrate data for advanced analytics, and apply Data Science techniques to build predictive models. Delivered AI applications driving improvements in business operations.

Designed, developed, and automated scalable ETL/ELT pipelines integrating data from multiple sources into cloud storage and data warehouses to ensure reliable data flow for analytics and AI applications. Orchestrated complex data workflows using Apache Airflow and AWS Batch with containerized tasks via Docker, enhancing scalability and performance. Applied data science techniques like exploratory data analysis, feature engineering, and model evaluation to support predictive models and AI workflows. Designed AI business applications including chatbots, sentiment analysis, and predictive models to improve customer interactions and operational decisions.