Rodrigo Blaudt

Rodrigo Blaudt

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location of Rodrigo BlaudtMaringá, Paraná, Brazil

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  • Timeline

  • About me

    Data Engineer @ GFT

  • Education

    • Universidade Estadual de Maringá

      2020 - 2022
      MS - Geography

      Developed supervised and unsupervised Machine Learning models to classify and analyse the landforms of Fernando de Noronha Island - Brazil.

    • Universidade Estadual de Maringá

      2016 - 2020
      Geography

      - Developed a Machine Learning model utilizing satellite data to estimate water quality, involving data extraction and pre-processing to correct for atmospheric effects. Published in Raega (A1).- Developed a geostatistical model to estimate data values for locations without direct measurements, based on nearby known values. Published in the Brazilian Cartography Journal (B2).

  • Experience

    • Datlo (YC S21)

      Feb 2020 - Nov 2023

      Developed new data products that retained 35% of the client base;Reduced customer churn rate by 2.5%;Created a service to enhance the customer experience with AI and ensure their journey's success. Developed and managed 5 innovation-focused proof-of-concept projects that won awards (Shell, Michelin, ZF Group, IFood).Lead the migration of on-premise applications to AWS Cloud and GCP Cloud.Improved ETL performance in 80% through code refactoring, table indexing, query improvement and architectural enhancements.Lead a team of 6 data engineers.

      • Head of Data and Analytics

        Jan 2022 - Nov 2023
      • Data Engineer

        Feb 2020 - Jan 2022
    • Compass UOL

      Dec 2023 - Apr 2024
      Senior Data Engineer

      Developed an API to transfer data between systems, improving data flow and reducing manual processing time by 60%.Built data pipelines to power dashboards, enabling managers to track stock performance daily.Mapped the schema conversion required to migrate a monolithic database to a microservices architecture.

    • GFT Techonologies

      Apr 2024 - now
      Senior Data Engineer

      Reduced AWS Cloud costs by 15% through redesigned data pipelines.Automated data quality validations in 80% of pipelines, aligning with internal standards.Implemented unit tests across all applications, achieving coverage above 75%.Integrated DataDog to enhance data observability in 40% of applications.

  • Licenses & Certifications

    • Building Modern Data Analytics Solutions on AWS

      Amazon Web Services (AWS)
      Oct 2024
    • Generative AI Fundamentals

      Databricks
      Feb 2024