Rafael Rosa Da Silva

Experience

• 

  Universidade Tecnológica Federal do Paraná

  Aug 2019 - Sept 2020

  Undergraduate Research Project

  I conducted research in Computational Intelligence, specifically focusing on Semantic Segmentation Networks for identifying defects in welds of oil pipelines. As a result of this study, I published a paper at the Encontro Nacional de Inteligência Artificial e Computacional (ENIAC), which is available at this link https://doi.org/10.5753/eniac.2020.12170

• 

  Dextra

  Jan 2021 - Nov 2021

  Data Engineering Intern

  I was part of an internal project at Dextra, where I worked on activities related to both Data Science and Data Engineering. I performed maintenance on the existing ETL pipeline and developed new ones. Additionally, I conducted Proofs of Concept (PoCs) and implemented Machine Learning models, primarily to classify Contact Reason.

• 

  CI&T

  Dec 2021 - now

  Within the AB-Inbev team, I performed tasks related to creating and maintaining ETL pipelines in an Azure environment. This involved developing code, creating jobs using Azure Databricks, and orchestrating workflows via Azure Data Factory and Databricks Workflows. I extracted data from MongoDB and made it available to various teams through Unity Catalog. Additionally, I supported the team by refining and developing activities, offering solutions to problems, and sharing knowledge. I started working in AB-Inbev and transitioned to Data Engineering. My responsibilities included creating and maintaining ETL pipelines in an Azure environment. This involved developing code and creating jobs using Azure Databricks; and orchestrating workflows via Azure Data Factory. The goal was to provide high-quality data to the team and to other teams. Additionally, I was involved in unit test creation and performance enhancements for Pyspark jobs. I was promoted to Data Scientist, and I continued to engage in activities related to Proofs of Concept (PoCs) and Machine Learning model implementations. My primary focus was on sentiment analysis and contact reason. I transitioned to Data Science, and undertook tasks such as story refinement, considering client needs and software requirements. Additionally, I conducted Proofs of Concept (PoCs) for Machine Learning models, analyzing performance metrics, parameters, and the databases used to assess feasibility for production implementation. I also implemented ML models in production, utilizing MLFlow for model versioning. I joined another project within the company, where I performed tasks such as story refinement, considering client needs and software requirements. Additionally, I was involved in creating and maintaining ETL pipelines, from developing data transformations to designing workflow templates, jobs, and orchestration.

  • Senior Data Engineer

    Apr 2024 - now

  • Data Engineer

    Apr 2023 - Apr 2024

  • Data Scientist

    Oct 2022 - Apr 2023

  • Junior Data Scientist

    Aug 2022 - Oct 2022

  • Junior Data Engineer

    Dec 2021 - Aug 2022