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Heyyo, I'm Luana 👋

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I'm a data scientist and engineer passionate about technology and innovation. Currently, I'm seeking to develop my career as a Data Engineer, aiming to explore different data technologies.

⚡Technologies

📋 Programming Languages

Python C Java JavaScript LaTeX

🧑‍💻 Data Science and Engineering Tools

NumPy Pandas Matplotlib scikit-learn TensorFlow DBT Apache Spark Apache Kafka Databricks Flask Airflow

💾 Databases

Postgres MySQL MongoDB ApacheCassandra

🎓 Education

  • Bachelor’s Degree in Electrical Engineering (UESC)
  • Master’s Degree in Electrical Engineering (UFMG)
  • Technical Course in Informatics (IFBA)
  • Specialization Course in Data Engineering (Ada Tech / Santander Coders)

🛠️ Working on

  • Projects involving data analysis and science, Big Data and research development in Renewable Energy and Atmospheric Sciences

    📚 Frameworks and Libraries: Xarray, Dask, Seaborn, NetCDF4, Google Earth Engine, Geopandas, Cartopy, Basemap

  • Projects using Databricks, ETL and ELT, data pipelines, APIs, basic event-driven data architecture and use of Webhooks, Data Quality, Data Clean, data validation with Great Expectations and data specialization through the Data Build Tool (DBT)

    📚 Frameworks and Libraries: PySpark, Great Expectations, Requests, SQLAlchemy, DBT

📖 Learning

  • Developing my skills in data engineering, focusing on Data Extraction, Analytics Engineering and Big Data

⚡ Fun fact

  • Besides my passion for data, I also enjoy spending my free time playing the guitar and enjoying a beautiful beach.

Luana Kruger's Projects

account_balance_report icon account_balance_report

Desenvolvimento de uma arquitetura distribuída para um relatório de saldo mensal de contas, utilizando Databricks, Spark, SQL e Great Expectations, para gerenciar eficientemente dados de saldos mensais de contas entre Jan/2020 e Dez/2020, permitindo consultas e análises rápidas para suporte à análise do comportamento do cliente.

cardata-cleaning-quality-automation icon cardata-cleaning-quality-automation

Projeto de limpeza e verificação de qualidade de dados de ofertas de carros usados na Alemanha. Inclui: 1. Limpeza de dados (remoção de inconsistências e duplicatas); 2. Verificação de qualidade com Great Expectations e; 3. Automação do processamento com DBT.

rio_airbnb-data_pipeline- icon rio_airbnb-data_pipeline-

Desenvolvimento de uma solução de engenharia de dados e garantia de qualidade para dados do Airbnb no Rio de Janeiro, utilizando a arquitetura medallion com PostgreSQL para armazenamento, dbt e Great Expectations para limpeza, transformação e testes de qualidade, organizados em camadas Bronze, Silver e Gold para análise eficiente.

wikipedia-web-scraping icon wikipedia-web-scraping

Este projeto implementa um script Python para automatizar a aquisição de dados de uma página da Wikipedia. Utiliza Selenium para navegar até a página, BeautifulSoup para extrair tabelas relevantes do conteúdo HTML, e pandas para processar e analisar os dados extraídos.

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