I'm a data analyst with a software engineering background, transitioning from full-stack web development into analytics. I build end-to-end data projects using SQL, Python, and Power BI — combining analytical rigor with the engineering discipline I've developed over years of shipping production code.
I take raw data and turn it into insights. I'm comfortable moving across the full stack:
- SQL — writing business-driven queries, window functions, CTEs
- Python — pandas EDA, statistical analysis, visualization (matplotlib, seaborn)
- Power BI — interactive dashboards, data modeling, stakeholder-facing reporting
My engineering background means I care about reproducibility, clean code, proper data pipelines, and knowing why a number matters, not just what it is.
Building a portfolio of real analytical projects, each one integrating SQL → Python → Power BI. My first project analyzed 2,500 OTT streaming titles across Netflix, Prime Video, and Hotstar — uncovering patterns in content strategy, platform performance, and audience behavior.
📊 OTT Streaming Analytics — SQL + Python + Power BI analysis of content trends and platform performance across 2,500 titles. Includes interactive dashboard, detailed findings, and full reproducible pipeline.
(Web dev projects below — solid foundation, but my focus is now on data.)
Data: SQL · Python (pandas, matplotlib, seaborn) · Power BI · SQLite
Engineering: JavaScript · React · Node.js · Git
If you're interested in data work, analytics projects, or the web-to-data transition story, reach out — I'm always up for discussing methodologies, tools, or interesting datasets.
Last updated: 23 June/2026