- Worked on data engineering projects in the financial sector, focusing on reliability, performance, and scalability of analytical systems. - Responsible for implementing and maintaining pipelines in AWS environment, using Lambda Functions and DAGs to trigger ingestion, transformation, and data delivery processes. - Developed data delivery solutions for the client's clients, ensuring data quality, integrity, and automated delivery. - Supported governance and standardization of cloud-based data flows, directly impacting critical business processes. - Participated in technical and strategic decisions related to data architecture, contributing to scalability and operational efficiency. - Worked in alignment with compliance and performance needs in the financial sector, delivering sustainable and high-value results.

- Worked on predictive modeling and analytical infrastructure for large-scale data environments. - Developed predictive models using advanced statistical techniques and machine learning algorithms to support strategic decision-making. - Participated in the implementation and optimization of Data Lake infrastructure, ensuring scalability and governance. - Used Azure and GCP cloud platforms to integrate, process, and automate analytical workflows. - Collaborated with multidisciplinary teams on strategic data projects across various sectors. - Consolidated skills in analytical engineering, predictive pipelines, and cloud data architecture.

- Worked on predictive analytics and fraud prevention projects in the energy sector. - Developed predictive models applying advanced statistical techniques and machine learning algorithms to detect fraud in consumption and internal systems. - Used web scraping and unstructured data extraction techniques to enhance coverage and efficiency of analyses. - Prepared and structured large-scale data for performance-focused and automated analysis. - Generated strategic insights for security and compliance departments by integrating operational and external data. - Strengthened skills in applied analytics, loss prevention, and risk-based predictive modeling.

- Worked on data engineering and cloud computing projects for major clients across different industries. - Deployed and managed infrastructure in Azure and AWS with a focus on data solutions. - Built ETL processes and Big Data pipelines using Scala and Python with Apache Spark and Databricks. - Developed scalable solutions for data ingestion, transformation, and governance. - Key projects included: multinational retail company (data governance architecture); national bank (Open Banking ingestion pipelines); telecom (geospatial analytics for network expansion planning). - Solidified expertise in data engineering, cloud computing, and large-scale data integration

- Worked on healthcare data projects involving analytics, visualization, and applied machine learning. - Performed data manipulation and analysis using Python and SQL, including cleaning, transformation, and exploratory modeling. - Created dashboards and reports in Power BI for tracking operational and clinical KPIs. - Developed a hybrid model for identifying pregnant women in the patient database, combining statistical filters based on clinical protocols and a custom neural network. - The model identified 90% of pregnancies and enabled early interventions in high-risk cases, helping reduce costs associated with complications. - Supported ETL processes and use of AWS services for clinical data storage and processing.

- Worked on data science and innovation projects in healthcare, focusing on clinical, operational, and genomic data analysis. - Developed exploratory analyses and predictive models using Python stack (Pandas, NumPy, Matplotlib, Scikit-learn). - Provided technical support in a genetic mapping and analysis project, including organization and analysis of biological data. - Produced weekly analytical reports on user behavior and app usage across the institution. - Created interactive dashboards for executive leadership to support data-driven decisions. - Collaborated with multidisciplinary teams focused on applied research and hospital innovation.