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luthfiraditya/README.md

Luthfi Raditya Meza


Senior Data Engineer



About ๐Ÿ‘‹

๐Ÿ“ซ I'm a Senior Data Engineer, a data engineering and systems integrator consulting firm based in Jakarta. I started in data science and machine learning, and today I spend most of my time building lakehouse platforms and data migrations for retail and enterprise clients in Indonesia, mainly on Databricks and AWS.

I lead a cross-functional team of engineers, from sprint planning to mentoring junior and mid-level engineers, and I'm also the internal Databricks technical authority at Insignia. I split my time between client discussions (pre-sales, architecture, scoping) and hands-on implementation. Outside of work, I enjoy sports, reading non-fiction, and binge-watching.

  • ๐Ÿ”ญ Currently working on lakehouse platforms, warehouse migrations, and cost optimization on Databricks and AWS
  • ๐ŸŒฑ Currently deepening my Databricks and AWS data engineering skills
  • ๐Ÿงญ Happy to talk about data architecture, migrations, and building data teams
  • ๐Ÿ“ I write on Medium
  • ๐Ÿ’ฌ Ask me about anything.

๐Ÿ’ป Languages and Tools: ๐Ÿ› ๏ธ

Databricks Spark AWS Airflow Snowflake dbt PostgreSQL Power BI Python MLflow Git GitHub Visual Studio Code


๐Ÿง Knowledge of:

Lakehouse Architecture, Medallion Architecture, Data Warehouse Migration, CDC Pipelines, Cloud Cost Optimization, Data Modeling, Data Engineering Team Leadership, Pre-sales & Solution Scoping, Machine Learning.


๐Ÿ“ Latest Blog Posts



๐Ÿ“ˆ GitHub Stats


Luthfi's GitHub Stats

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  1. Ecommerce-Recommendation-System Ecommerce-Recommendation-System Public

    I built recommender systems for recommending products to user using Model-based recommendation system.

    Jupyter Notebook

  2. Uber-vs-Green-Cabs-Trip-in-New-York-City Uber-vs-Green-Cabs-Trip-in-New-York-City Public

    Analyzing the performance of Green Cabs and Uber Taxi through visual analysis of passenger trips using Green Cabs and Uber Taxi from January to June in 2015 in the New York City area.

    Jupyter Notebook

  3. Market-Basket-Analysis Market-Basket-Analysis Public

    Identified and analyzed 32+ millions row data product for customer order prediction. Create visualization on jupyter using seaborn and matplotlib an dashboard in tableau.

    Jupyter Notebook

  4. Attrition-Turnover-Prediction Attrition-Turnover-Prediction Public

    Conducted analysis and predictions related to turnover on employee data in a company.

    Jupyter Notebook

  5. Location-Recomendation-for-Retail Location-Recomendation-for-Retail Public

    Build location recommendations for retailers who want to open offline stores.

    Jupyter Notebook

  6. Herd-Immunity-Prediction Herd-Immunity-Prediction Public

    Create model to predict the herd immunity based on vaccines rate in Indonesia.

    Jupyter Notebook