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Built a local tech stack tool to complete ELT data pipeline of any kind. The tools consist of MySQL, PostgreSQL, dbt, Spark, Airflow and Docker

Python 40.91% Dockerfile 0.15% Shell 0.17% Makefile 0.04% JavaScript 33.33% CSS 0.08% Less 6.62% TypeScript 17.57% HTML 1.11% Mako 0.02%
airflow big-data data-pipeline datawarehouse dbt docker mysql-database postgresql spark

data-tech-stack-tools's Introduction

Hi, I am Abubakar Alaro

  • 📖 I love writing codes, creating Data Pipelines (ETL, ELT, EL EtLT) and Tutoring PS: Alumni @10Academy
    💻: Data Engineer
    and learning continues... Loves Cats 🐱 :octocat:
  • 🔭 creating production ready pipeline for automating data extraction, loading and transformation using tools like Apache Airflow for Orchestration, dbt for Transformation & Spark for Big Data Processing with some BI tools such as Tableau, Data Studio, Superset for Visualization and Insights Communication.
  • 🌱 practicing Data Engineering with CSPs like GCP and AWS using tools that includes EC2, S3, EMR, MWAA, CloudFormation, DataProc, DataFlow, BigQuery, BigTable just to mention but a few.
  • 👯 In my free time, I like to build data tools(Open Source Contributions), learn about platform design and system architecture designs, and pipelines that can help transform business into being data-powered.
  • 💬 Ask me about topics related to Data Science, Machine Learning, Data Engineering, Platform Design, Cloud Computing, Big Data, Data Pipeline Architecture
  • 🏢 Linkedln
  • ⚡ Fun fact:
    • 😂 i'm addicted to learning and improving every day
    • 📝 i love to see others grow and improve
  • Exploring Scala for Big Data Analytics
  • Learning how to build Data Platform to better deliver quality service to users

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