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KevenGustavo/README.md

Hi, I'm Keven Gomes 👋

Data Engineer | Analytics & Process Automation

📍 São Luís, MA, Brazil | 🎓 Computer Engineering Student

LinkedIn Email


I specialize in architecting highly available data infrastructure and building automated ETL/ELT pipelines. Combining my academic background in Computer Engineering with hands-on experience in business logic, I focus on bridging the gap between robust data architecture and scalable, real-world solutions.

Beyond cloud infrastructure, I have a strong track record of transforming manual, error-prone operational bottlenecks (like industrial or logistics tracking) into reliable, automated workflows and real-time dashboards for decision-makers.

🛠️ Core Tech Stack

Python dbt Apache Airflow Docker
Microsoft Azure Google Cloud Apache Spark
PostgreSQL SQL Server MongoDB

🚀 Featured Architecture & Pipelines

  • E-Commerce Modern Data Stack: End-to-End Analytics

    • Stack: Apache Airflow, dbt Core, PostgreSQL, MongoDB, Metabase, Docker & Astro CLI
    • Architecture: Engineered a robust ELT pipeline extracting nested JSON documents from a transactional NoSQL database into a structured Data Warehouse. The pipeline follows the Medallion Architecture and utilizes Astronomer Cosmos to translate dbt models into visual Airflow TaskGroups, actively solving engineering bottlenecks like XCom Bloat and grain changes.
  • SQL Data Warehouse: Medallion Architecture

    • Stack: SQL Server 2022, Python, Docker, Star Schema
    • Architecture: Developed a production-ready pipeline that integrates disjointed raw data from CRM and ERP systems into a centralized Star Schema based on the Kimball Methodology. Built strict data quality gates to actively check for left-join fan-outs and ensure absolute referential integrity across the Bronze, Silver, and Gold layers.
  • PostgreSQL High-Availability & Chaos Engineering

    • Stack: PostgreSQL 16, Patroni, etcd, HAProxy, Docker Compose, Python
    • Architecture: Engineered a strict CP-Distributed Consensus cluster (Raft) guaranteeing Zero Data Loss (RPO=0) and automated sub-30s failover (RTO). Includes a custom SRE Chaos suite to physically audit network partitions and orchestrate self-healing without Split-Brain.

🌱 Currently Expanding My Stack

  • Deepening knowledge in distributed data processing with Apache Spark.
  • Exploring modern Lakehouse architectures on Azure Databricks.
  • Structuring automated reports and business logic dashboards for operational efficiency.

📊 GitHub Analytics

GitHub Extended Stats Top Languages

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  1. data-warehouse-project data-warehouse-project Public

    An automated Enterprise Data Warehouse built from scratch. Implements Medallion Architecture (Bronze, Silver, Gold), Star Schema modeling, and a Python-driven ETL pipeline using SQL Server and Docker.

    TSQL

  2. mds-mongodb-dbt-project mds-mongodb-dbt-project Public

    Pipeline analítico End-to-End (ELT) simulando um e-commerce. Extração do MongoDB para PostgreSQL orquestrada via Airflow (Cosmos), com modelagem e testes em dbt Core, e BI no Metabase.

    Python