Mauricio Benegas

Direct contractor to CVS Health; individual contributor since February 2025. Design and operate ELT/ETL pipelines and analytical datasets on GCP and Snowflake. Build incremental SQL models, reconcile and validate source-to-target data, troubleshoot production issues, and contribute to data quality, governance, testing and CI/CD.

Built and optimized Snowflake data models and ELT workflows for financial, customer, marketing and ML use cases. Delivered production datasets with Python, SQL, dbt, Airflow, AWS, Snowflake and Matillion. Partnered with product, marketing and finance teams to define maintainable models, data contracts and trusted metrics.

Developed BigQuery/dbt analytical models and production pipelines with Python, SQL, GCP, AWS and Airflow/Cloud Composer across Argentina, Mexico and Colombia. Modeled payments, customer, financial and marketing data with emphasis on quality, performance and downstream usability.

Led the development of a query that enabled proactive collection of $103M USD in outstanding debt from charged-back processes across Latin American markets, significantly boosting P&L. Collaborated on establishing and monitoring KPIs, which increased overall operational efficiency by 15%. Automated manual advertising processes with Python, reducing calculation time by 80% and enhancing collection

Leveraged data analytics to provide insights to multiple companies, resulting in a 25% increase in data-driven decision-making and operational efficiency improvements. Applied SixSigma methodologies to 10 companies, achieving a 40% reduction in defects and a 20% increase in overall product quality.

Performed comprehensive data analysis for various government processes, contributing to informed decision-making. Developed and maintained SQL databases to support data management and reporting needs.

Studied core principles of industrial engineering, focusing on optimizing production processes, logistics, and quality control. Developed skills in operations research, supply chain management, and system analysis to improve organizational efficiency.