- Application of knowledge in Requirements Engineering, Software Development Methods, Object Orientation, Programming Techniques, Maintenance and Evolution, Verification and Validation, Measurement and Analysis, Architecture, and Configuration Management.
- Use of multi-agent systems for solving distributed constraint optimization problems.
- Leading a team of data professionals, responsible for talent selection, onboarding, individual monitoring, and team backlog management.
- Architecting and leading the implementation of a Data Lakehouse for the company, centralizing customer information, financial transactions, investments, and other applications using AWS, Nifi, Spark, and Databricks.
- Implementing CI/CD for deploying data tools and products developed by the team using Gitlab CI, Docker, and AWS tools.
- Developing and deploying a mathematical optimization system that, based on clients' financial situations, automates financial planning, making the planning process scalable.
- Training the team to write software tests using Pytest, increasing test coverage of applications.
- Creating a ranking of investment advisors to guide their actions according to the company's strategies using SQL.
- Creation and maintenance of ETL data pipelines from various sources.
- Deployment of Apache Airflow on AWS Elastic Beanstalk (EBS) to orchestrate routines using Docker.
- Development of Python packages to perform variable commission calculations for advisors, simplifying the work of the finance department.
- Implementation of Google Analytics on the company's websites to monitor traffic and maximize the effectiveness of marketing campaigns.
- Creation of data reports with company KPIs to assist in decision-making.
- Working in the research team at IBPAD, developing ETLs, analyses, and data visualizations for client companies using Google BigQuery.
- Developing packages for processing textual data, identifying entities, categorizing texts, and generating graphs using Scikit-learn, Pandas, Spacy, and Networkx.
- Developing applications for data scraping from various sources using Scrapy.
- Creating entity clustering models using Scikit-learn.