Computer Engineering student at Chulalongkorn University
Focused on building scalable ETL pipelines and AI-powered analytics systems.
An end-to-end data platform unifying ETL, Star Schema Modeling, and LLM-powered Insights.
I integrated my previous work on data cleaning, strategic analysis, and AI development into one comprehensive ecosystem. This project demonstrates my ability to handle the entire data lifecycle.
Key Achievements:
- ποΈ Robust ETL Pipeline: Built modular Python/Pandas workflows to extract and validate 100k+ records from raw Brazilian e-commerce data into PostgreSQL.
- π Architectural Modeling: Designed an analytical Star Schema (Fact & Dimension tables) to optimize complex revenue queries and RFM segmentation.
- π‘οΈ Secure AI Assistant: Integrated OpenAI API with Streamlit to convert natural language to SQL, featuring a safety validation layer to prevent destructive commands (DROP/DELETE).
- π Actionable Insights: Automated the generation of business KPIs and interactive Plotly visualizations directly from chat prompts.
Tech Stack: Python Β· PostgreSQL Β· Streamlit Β· OpenAI Β· SQLAlchemy Β· Pandas
- Data Engineering: Incremental loading, performance optimization, and pipeline orchestration.
- Data Modeling: Designing efficient relational schemas (OLAP) for business intelligence.
- AI Integration: Building safe and reliable LLM-based interfaces for data exploration.
- βοΈ Scaling data workloads using AWS (EC2/S3).
- π Mastering workflow orchestration with Apache Airflow.
- π§ Strengthening Linux systems administration and deployment.


