"Identifying operational inefficiencies and architecting full-stack data pipelines to create lasting value."
Building resilient, low-latency ETL frameworks and relational schemas that serve as the backbone for enterprise intelligence.
The core differentiator. Orchestrating complex logic between SaaS tools, APIs, and local databases using self-hosted automation engines.
I apply First-Principles thinking to break down complex institutional problems into modular, logical components that can be automated away.
Architected a professional-grade desktop application integrating PyQt5 for the GUI and Ollama for local LLM inference. Transforms natural language queries into complex Excel formulas without data ever leaving the local machine.
# Initiating Ollama local inference...
> User_Input: "Calculate rolling 3-month variance"
> Backend: PyQt5 Signal Received...
> Model: Llama3:Instruct context loading...
> Output: =VAR.P(OFFSET(A1,0,0,3,1))
Production-grade, fully automated data pipeline that scrapes daily data, updates a persistent SQL database, and commits a live analysis report with zero human touch.
>> Architected the Medical Data Management System (MDMS) using n8n for ETL orchestration and Django for secure data governance.
>> Engineered the Booking Data Pipeline to synchronize core platforms, ensuring 100% data consistency and reliability across distributed systems.
>> Spearheaded enterprise automation for regulatory reporting, resulting in an immediate 80% reduction in manual workload.
>> Developed the 'GEM Automation Code' engine, successfully managing 29,000+ policies via robust RESTful API integrations.