Lucas Alves

I lead multidisciplinary teams responsible for the institution's digital transformation, managing projects spanning data analysis, software development, and automation of educational and administrative processes. Challenge: internal processes relied on manual data transfers and management had no real-time visibility into student performance indicators. Actions and deliveries: - Managed the full project lifecycle for data engineering and software development initiatives using Scrum and Kanban, ensuring on-time delivery within defined scope - Coordinated implementation of a Python ETL pipeline with SQLAlchemy for automated migration of school system data to PostgreSQL, eliminating manual rework - Supervised the development of a JavaScript API with SQL queries that generated interactive student performance dashboards, delivering unprecedented analytical visibility to school management - Structured version control processes with GitHub, standardizing the team's development workflow Managed stack: Python, JavaScript, SQL, PostgreSQL, REST API, Selenium, GitHub, Scrum, Kanban.

Continuation of urban mobility data work focused on optimizing existing pipelines and continuously improving the quality of data delivered to clients. Ongoing actions: - Optimization of ETL pipelines in Python and Amazon Redshift, reducing processing bottlenecks and increasing data reliability for municipal clients - Monitoring and maintenance of electronic ticketing data quality from inumerous cities - Documentation of data engineering processes to ensure traceability and facilitate solution scalability Stack: Python, SQL, Amazon Redshift, PostgreSQL, Pandas, Knime, DuckDB Keywords: Data Analysis · ETL · Amazon Redshift · Python · Knime · Web Scraping · Selenium · Data Warehousing · Urban Mobility

Responsible for the integration, analysis, and storage of urban mobility data serving clients across Brazil. - The company needed to integrate heterogeneous data sources from dozens of cities to generate mobility analyses. I developed and optimized ETL pipelines using Python, Knime, and Amazon Redshift, centralizing data and ensuring availability and reliability for client decision-making. - Client cities needed to understand passenger behavior on public transit. I conducted data analysis of the "Boarding/Alighting" survey, identifying boarding and alighting patterns that guided decisions on route planning and scheduling. - Manual data collection was common in some areas. I automated the process through web scraping with Python and Selenium, reducing data acquisition time from hours to minutes. - New team members had difficulty understanding existing data flows. I provided technical support and documented processes, contributing to the standardization of workflows and the team's growth. Stack: Python, SQL, Amazon Redshift, PostgreSQL, Pandas, Knime, DuckDB Keywords: Data Analysis · ETL · Amazon Redshift · Python · Knime · Web Scraping · Selenium · Data Warehousing · Urban Mobility

Responsible for the institution's data infrastructure and administrative process automation. - School system data was isolated and inaccessible for analysis. I created a Python pipeline with SQLAlchemy that automatically migrates data to PostgreSQL, centralizing information and eliminating manual transfers that consumed 2/3 of the team's time per week. - School management had no visibility into student indicators. I developed a JavaScript API with SQL queries that generates interactive charts, enabling visual analysis of student performance for the first time. - I took on full database administration (installation, configuration, monitoring, and optimization), ensuring continuous availability and performance. - Electronic invoice issuance (NFs-e) was done manually through the WebISS system, consuming administrative staff time. I automated the entire process with Python, eliminating manual work that consumed 5 full days of the team's time per month, and reducing errors by zero. - External data needed to be collected periodically from web sources. I implemented web scraping with Python and Selenium, automating collection that was previously done manually. Stack: Python, SQLAlchemy, PostgreSQL, JavaScript, HTML5, SQL, Git. Keywords: PostgreSQL · SQLAlchemy · JavaScript · API Development · Database Administration · Python · Automation · NFs-e · Web Scraping

I created automation tools that scaled the company's commercial operation. - The sales team sent messages manually on WhatsApp, limiting the daily volume of contacts. I developed bots in Python with Selenium and PyQt5 that automated message sending and bulk number validation, multiplying the team's prospecting capacity by 10x. - Sending spreadsheets between departments over the local network was manual and error-prone. I built a system with PyQt5, SQLite3, and Pandas that automated file handling and delivery, eliminating errors and freeing up 20 hours of the team's tjme per week. - Customer service through WhatsApp was entirely manual. I developed a chatbot in JavaScript with wa-automate-js, automating frequent responses and reducing response time. Stack: Python, Selenium, PyQt5, Pandas, SQLite3, SQL, JavaScript, CSS, GitHub, OOP. Keywords: Python · Selenium · Automation · Chatbot · PyQt5 · SQLite · Pandas · JavaScript · RPA