Managed a 40-person team, including Business Intelligence Engineers, Data Scientists, Data Engineers, and Machine Learning Engineers, focused on building a data mesh architecture to enable scalable and decentralized data analysis.Key Projects: Participated in defining improvements in data pipelines through the application of DataOps, MLOps, and data governance principles, enhancing data lifecycle efficiency and quality across the company.Implemented Generative AI (Gen AI) models for communication automation, optimizing operational processes and reducing response times by 40%.Key Integrations: Led the integration with Google Cloud Platform (GCP), Astronomer, DBT, and Gemini, establishing a robust and scalable cloud infrastructure.Tech stack used: MySQL, PostgreSQL, Airflow, BigQuery, Composer, GitHub, Astronomer, DBT, Atlan, GCP ML.Implemented advanced data governance solutions, ensuring data integrity and security, facilitating collaboration across teams and business units.

Managed a multidisciplinary team of 25 people, including Business Intelligence Engineers, Data Scientists, Data Engineers, and Machine Learning Engineers, focused on building a data mesh architecture that enabled decentralized and scalable data analysis.Key Projects: Created the Machine Learning Engineering team within the company and defined key improvements in supply models, demand forecasting, routing, and topology. These improvements enhanced forecast accuracy and operational efficiency by 25%.Key Integrations: Led the integration with Google Cloud Platform (GCP), enhancing cloud infrastructure to support higher data processing volumes.Tech stack used: MySQL, PostgreSQL, Airflow, BigQuery, Composer, GitHub.Drove the development of new predictive models to optimize delivery routing and efficiently manage supply resources, resulting in a significant reduction in operational costs.

Led a 6-person BI team focused on building a data mesh architecture, enabling greater scalability and decentralization of data management.Key Projects: Achieved 100% migration to Looker BI, defined best development practices, and significantly improved Data Warehouse architecture, optimizing query and processing times.Key Integrations: Spearheaded the integration with Google Cloud Platform (GCP), enhancing cloud infrastructure for reliability and scalability.Tech stack used: MySQL, PostgreSQL, Airflow, BigQuery, Composer, GitHub.Implemented a best practices framework for BI development, ensuring consistency and high quality in deliverables.

• Creation of reports and analysis of information systems that allow decision-making based on data.• Things I built: Logistics, User & Revenue Retetion Report, Customer Contact Prioritization System • Integrations: Migration to Looker BI• Stack includes: BigQuery, Airflow, QlikView, Looker