I am an experienced Software Engineer with a strong foundation in Python and SQL, specializing in backend and API development for data-intensive applications. With over 10 years of experience, I have designed and maintained RESTful APIs using frameworks like Django and Django Rest Framework. My expertise extends to relational databases, including PostgreSQL and MS SQL Server, where I have proven my ability to optimize queries and integrate with legacy systems. I am known for my clear communication skills, cross-functional collaboration, and a proactive approach to troubleshooting and performance optimization. Throughout my career, I have delivered robust, scalable solutions in healthcare and research environments, ensuring that I meet the needs of diverse stakeholders.
– Senior Developer of SUAP, a national-scale ERP platform supporting administrative and academic operations across multiple Federal Institutes in Brazil.
– Architected and maintained backend modules using Python and Django, enabling scalability and maintainability of core institutional services.
– Designed relational database schemas and wrote optimized PostgreSQL queries, views, and stored procedures to support analytics and reporting.
– Applied Behavior-Driven Development (BDD) with behave and implemented unit tests to improve code quality and ensure test coverage.
– Delivered full-stack solutions using HTML, CSS, JavaScript, and modern design patterns for dynamic, user-friendly interfaces.
– Managed the complete SDLC, from technical planning and implementation to deployment and long-term maintenance across multiple campuses.
– Leading end-to-end development efforts for a large-scale telehealth platform, with a strong focus on backend architecture, API integration, and data-driven features.
– Designed and maintained scalable backend systems using Python and Django, ensuring robust integration with health data pipelines.
– Led sprint planning, code reviews, and mentoring sessions to align the team with Agile best practices and continuous delivery.
– Acted as a bridge between technical and non-technical stakeholders, translating health domain requirements into well-scoped, actionable technical tasks.
– Oversaw DevOps processes and CI/CD pipelines via GitLab, ensuring code quality, traceability, and efficient deployment cycles.
– Implemented performance monitoring strategies and contributed to data modeling for better system resilience and stakeholder reporting.
– Developed a data analysis platform to assess public health interventions using machine learning and NLP techniques.
– Built a modular data processing ecosystem using Python, integrating Scrapy, Pandas, and NLTK to collect, clean, and transform large-scale unstructured news data.
– Applied Natural Language Processing (e.g., sentiment analysis with VADER, TF-IDF, DBSCAN clustering) to extract insights from media coverage on public health topics.
– Conducted statistical analysis (including Interrupted Time Series and segmented regression) to evaluate the impact of national health campaigns.
– Designed interactive visualizations using Matplotlib and Plotly to support decision-making for stakeholders.
– Automated data workflows and configured CI/CD pipelines with GitLab, ensuring reproducibility and deployment efficiency.
– Contributed to the development of scalable web systems supporting health and social service management in Brazil.
– Developed web applications using Python and the Django framework, following clean architecture and modular design.
– Built and consumed RESTful APIs, ensuring seamless integration between frontend and backend services.
– Designed, normalized, and optimized PostgreSQL databases to support complex business logic and data integrity.
– Wrote unit and integration tests to maintain code quality, reliability, and test coverage across multiple components.
– Participated in Agile/Scrum cycles, including sprint planning and retrospectives, contributing to team velocity and deliverable tracking.
– Created and maintained technical documentation for system features, architecture decisions, and API specifications.
– Collaborated with non-technical stakeholders to gather requirements and translate them into functional technical solutions.
– Mentored junior developers, promoting adherence to coding standards and best practices.
– Supported academic research through the design of data pipelines and analytical tools for policy and behavioral studies.
– Developed data ingestion tools in Python, integrating data from REST APIs and web scraping via Scrapy for structured analysis.
– Conducted both qualitative and quantitative analysis, transforming raw datasets into actionable insights.
– Researched and evaluated emerging machine learning frameworks for use in academic and social data contexts.
– Designed data visualizations, spreadsheets, and presentation materials to clearly communicate findings to diverse audiences.
– Actively contributed to research meetings and knowledge exchange sessions with faculty and technical teams.
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