Experience
Data Engineer at Nationale-Nederlanden
Madrid, Comunidad de Madrid, Spain
- Specialist in Data Engineering, with a solid background in software engineering.
- Construction of a Data Mart, using Microsoft Azure tools such as Azure Data Factory, Databricks, and SQL Management.
- Committed to technological innovation and business intelligence, optimizing data solutions aligned with the company's strategic goals.
- Proficient in Databricks, SQL Server, SQL, Python, PowerBI, Data Warehouse, Microsoft Azure, Fabric, and Copilot.
- Continuously facing challenges, questioning traditional approaches, and advocating for continuous improvement.
Data Mining Researcher at IOTECH
Oporto, Portugal
- Collaborated with IOTECH on the ioCity project, a European Union-funded project focused on transforming urban mobility.
- Used CRISP-DM and SCRUM methodologies, applying advanced predictive modeling techniques.
- Performed meticulous data preparation, cleaning, and integration.
- Integrated gamification principles, designing tasks, missions, and rewards to encourage sustainable behaviors.
- Developed a real-time seat availability system, improving the user experience.
- The experience highlighted the importance of collaboration and knowledge expansion in dynamic environments.
- Contributed to the innovation and future of urban mobility, connecting academic knowledge with real-world applications.
Education
Bootcamp in Marketing Data Analytics at Universidad Internacional de La Rioja (UNIR)
- Dived into the tools of the Spanish market while revisiting some already known ones.
- Balancing professional commitments, the Bootcamp, and my master's thesis was a gratifying challenge.
- Mastered skills in linear regression, Machine Learning, and advanced Excel.
- Data management and analysis, databases with PostgreSQL, Tableau, PowerBI, Data Marts, and ETL with Spark.
- Conducted research and developed marketing projects using Google Analytics and Marketing Mix Modeling.
- Created predictive models to improve marketing strategies.
Master in Information Systems Engineering at Universidade do Minho
- Analyzed and designed information systems to solve common challenges.
- Applied machine learning to create predictive models and business intelligence.
- Visualized data effectively to facilitate deep analysis.
- Designed advanced cloud architectures for information systems.
- Implemented security measures with detection, prevention, and response tools.
- Explored and applied legal aspects to ensure compliance and technological integration.
Bachelor in Information Systems Engineering at Universidade do Minho
- Mastered fundamentals of computing such as Linear Algebra, Calculus, and Algorithms.
- Experience with matrix operations and advanced algorithms.
- Studied Database Management, Object-Oriented Programming, Operating Systems, and Computer Networks.
- Refined skills in Java and concurrent programming.
- Specialized in data analysis, distributed systems, and enterprise application deployment.
- Created robust distributed applications and visualized data effectively.
- Applied optimization algorithms to engineering problems.
- Solved real-world challenges, enhancing my technical and problem-solving skills.
- Used advanced algorithms on real datasets through elective courses.
Certifications
Oracle Cloud Infrastructure 2025 AI Foundations Associate (1Z0-1122-25)
Oracle Cloud AI certification obtained through the Race to Certification 2025. Ver en GitHub
Oracle Cloud Infrastructure 2025 Foundations Associate (1Z0-1085-25)
Oracle Cloud certification obtained through the Race to Certification 2025 challenge. View on GitHub
Big Data and Spark: Data Engineering with Python and PySpark
Certification in data engineering using Python and PySpark for Big Data management. Github
Azure Databricks & Spark For Data Engineers
Real World Project on Formula1 Racing using Azure Databricks, Delta Lake, Unity Catalog, Azure Data Factory Github
GitHub Projects
Azure Data Factory
A set of hands-on exercises using the Azure environment, focusing on Azure Data Factory to efficiently integrate and process data.
Published Articles
Smart Dashboards for Monitoring Occurrences in Smart Cities: A Portuguese Case Study
This article addresses the improvement of intervention requests for the Professional Fire Brigade in Lisbon through the creation of interactive dashboards. The results show that 58% of false alarms are canceled after activating emergency means and 97% of suspended requests are not canceled before the means are dispatched. Occurrence records increase over the years, with peaks on Sundays and in the autumn. More than 50% of occurrences happen outside administrative hours and usually only one vehicle is dispatched.