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Building AI-driven BI & scalable Data Pipelines
βš™οΈ
Building AI-driven BI & scalable Data Pipelines

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@JML-Data-AI

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jlandaa/README.md

Header

πŸ’« About Me

I bridge the gap between traditional Business Intelligence and modern, AI-driven data architectures to build scalable data products.

  • 🧠 Focus: Designing robust ETL pipelines, deploying predictive models (MLOps), and automating enterprise reporting.
  • βš™οΈ Impact: Proven track record of reducing manual data errors by up 60% and improving analytical response times by 50% in corporate environments.
  • πŸŽ“ Background: Computer Engineer (UADE) with advanced certifications in Data Governance, Quality, and Analytics.
LinkedIn Website Email

πŸ› οΈ Tech Stack & Tools

Data Engineering, ETL & Orchestration

Databricks PySpark Delta Lake Apache Airflow SSIS

Business Intelligence & Analytics

MicroStrategy Power BI Tableau Looker

Databases & Cloud

Google Cloud BigQuery Amazon Redshift PostgreSQL SQL Server

Programming, Data Science & Automation

Python XGBoost Selenium

CI/CD & DevOps

GitHub Actions Docker


πŸ† Certifications & Data Governance

  • MicroStrategy Certified Certified Project Architect, Administrator, Database Administrator, and ONE Professional.
  • Alation Certified Certified Professional - Consultant & Seller.
  • Soda Data Quality Cloud Fundamentals.

⚑ Current Focus

  • 🎯 Open to: Full-time corporate roles as a Data Engineer, Analytics Engineer, or Senior BI Developer.
  • πŸš€ Currently building: End-to-end data products integrating advanced ETL automation (Databricks/PySpark) with enterprise BI platforms, and deploying interactive Streamlit applications using Argentine market datasets (finance & public procurement).

πŸš€ Live Portfolio & Apps

Uptime

  • πŸ€– Sales AI Chatbot - Text-to-SQL & Visual Analytics

    πŸ› οΈ langchain bigquery docker gcp streamlit text-to-sql

  • πŸ“ˆ ADR Dashboard - Argentine Market Analysis

    πŸ› οΈ data-engineering etl-pipeline python streamlit financial-analysis

  • πŸ’³ Smart Credit ML - Predictive Model

    πŸ› οΈ xgboost mlops shap bigquery explainable-ai streamlit

  • πŸ›’ Retail Price Scraper - Automated ETL Pipeline (PySpark & Delta Lake) ETL Status

    πŸ› οΈ pyspark delta-lake powerbi web-scraping competitive-intelligence

  • βš™οΈ Portfolio Monitor - DataOps & CI/CD Automation

    πŸ› οΈ github-actions dataops ci-cd monitoring serverless selenium


πŸ“Š GitHub Stats


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  1. Sales-AI-Chatbot Sales-AI-Chatbot Public

    LLM Agent & Text-to-SQL Pipeline for BI Analytics. Built with LangChain, Google BigQuery, Docker, and Streamlit UI.

    Python 5

  2. Smart-Credit-ML Smart-Credit-ML Public

    End-to-End Credit Risk Scoring. Features XGBoost, MLOps (Data Drift), SHAP, and NLG Assistant. Deployed via Streamlit & BigQuery.

    Python

  3. ETL-ADR-Argentina ETL-ADR-Argentina Public

    Automated Data Pipeline (ETL) & Financial Dashboard. Engineered with Python, SQLAlchemy (SQLite), GitHub Actions, and Streamlit.

    Python 1

  4. Retail-SQL-Reporting Retail-SQL-Reporting Public

    Advanced SQL Analytics & BI Reporting for Retail. Engineered on Databricks Lakehouse utilizing Spark SQL and Data Warehousing techniques.

  5. Retail-Price-Scraper Retail-Price-Scraper Public

    Automated Data Ingestion & ETL Pipeline for Retail Intelligence. Engineered with PySpark, Delta Lake, Selenium/Scrapy, and Power BI.

    Python 1

  6. Automated-Alert-Bot Automated-Alert-Bot Public

    Lightweight Web Scraping & Alert Automation System. Built with Python, Requests, and Telegram API. Deployed on Google Cloud (Linux VPS) for 24/7 monitoring.

    Python