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castrokelly/README.md

Welcome, I'm Kelly!

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About me

I’m Kelly Castro 👋, a Data Engineer & DevOps enthusiast who loves turning complex data into clear, strategic insights. Over the past decade, I've designed and built cloud-native platforms on Microsoft Azure, always with an eye on delivering real business value.

At SLB OneSubsea, I modernized our ISO 50001 compliance process by automating energy-data ingestion and reporting. Using Event Hubs → ADLS Gen2 → Azure Databricks and Data Factory, I replaced weeks of manual work with real-time Power BI dashboards, cutting audit prep from days to hours.

I also led ARBOSOCIAL: an open-source arbovirus prediction system data-lab-org/ARBOSOCIAL. By integrating social, climate and health data, building ensemble ML models in PySpark and scikit-learn, and surfacing results in interactive notebooks, we achieved over 85% accuracy and supported early-warning efforts in pilot regions.

Most recently, I delivered a Quality Notifications platform in SLB OneSubsea, that slashed our SLA from 20 to 7 days and boosted operational efficiency by 15%. Streaming SAP alerts into Event Hubs, processing them with Databricks, and visualizing in Power BI (all provisioned via Terraform and CI/CD pipelines), our team now focuses on solving root causes instead of wrangling spreadsheets.

I thrive in Agile squads, collaborating with engineers, simulation experts and product teams. I’m fluent in Python, SQL, DAX and CI/CD tools (Azure DevOps, GitHub Actions), and I’m sharpening my Kubernetes skills in preparation for CKAD.

🔗 Resume: kelly.decastro.com.br

🔗 Stack Overflow: users/18042741/kelly-de-castro

Let’s connect! I'd love to explore how we can use data and DevOps to drive measurable impact together!

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  1. data-lab-org/ARBOSOCIAL data-lab-org/ARBOSOCIAL Public

    ARBOSOCIAL: Sistema Integrado de Análise e Predição de Arboviroses com Base em Determinantes Sociais

    Python

  2. MBA MBA Public

    Data Science - Notebooks

    Jupyter Notebook

  3. Data-Science Data-Science Public

    Abordagem Ensemble para Detecção e Classificação de Anomalias em Poços de Petróleo: um Estudo Aplicado ao Dataset 3W.

    Jupyter Notebook

  4. 42sp 42sp Public

    Basecamp (piscina)

    C 1

  5. Hackathon-Petrobras Hackathon-Petrobras Public

    O objetivo do hackathon é integrar esses dois projetos, utilizando a BibMon para detectar eventos presentes na versão 2.0.0 do 3W Dataset, recentemente lançada.

    Jupyter Notebook