Electrical engineer with a passion for programming and data. Experience in data engineering, ETL development, SQL databases, AWS, and Azure. Proven ability to design cloud and BI solutions.
Development of cloud-based Machine Learning and ETL solutions for the financial sector. Utilizing Azure SQL Database, Databricks, Data Factory, Analysis Services, Azure Functions, DevOps, Git, Integration Services, PostgreSQL, Python (PySpark, Pandas, NumPy, Scikit-Learn, Streamlit), Jenkins, Ansible, Docker, and agile methodologies (Azure DevOps and Jira).
Major achievementImplementation of ETL and Machine Learning solutions in Azure, using Databricks, Data Factory, PostgreSQL, Python and CI/CD tools such as Jenkins and Git.
ETL development for loading data into Azure SQL and AWS S3. Creation of Power BI dashboards connected to Athena and Azure SQL. Use of AWS Glue, Lambda, Power BI, SSIS, Python (Pandas, SQLAlchemy, NumPy).
Major achievementDevelopment of ETL processes with AWS Glue and SSIS, data integration in Azure SQL and AWS S3, dashboard design in Power BI.
Design of predictive tools to estimate electrical load and energy generation. Use of Python (Sklearn, PyTorch, Keras, Pandas, NumPy, SQLAlchemy, SciPy), SQL (SSMS, SQLAlchemy), Power BI, Excel, Git (Azure DevOps).
Major achievementBI and analytics support, development of predictive tools with Machine Learning and Deep Learning in Python, version control with Git.