I'm a SQL-first analyst with a computer science background. I enjoy turning raw data into dashboards people actually use, and I care more about writing code I can explain than code that just works.
I got into this by taking messy, half broken datasets and turning them into something a business could actually act on. Along the way I started automating the boring parts too, things like triggering ingestion jobs or sending out alerts, because running the same steps by hand every day felt like a waste of time.
I care more about being able to explain my work than making it look polished. If something is on my resume or in a project writeup, I can walk you through how I got there, the code behind it and where it falls short.
The part I keep coming back to is automation. I don't just want to analyze data, I want to build workflows that do the repetitive work for me, from ingest triggers to alert pipelines. I think analysts who understand this side of things end up being more useful.
An end-to-end analysis of ~829K toy transaction rows. Features an interactive dashboard and business report diving deep into monthly trends and category shares.
An automated data processing pipeline engineered to flag suspicious transactional activity. Built using Databricks to clean and query anomalous behavior.
An intelligent chatbot named Nova engineered entirely in n8n. Interfaces Gemini LLMs and Pinecone vector indexes for context-rich data answering.
An end-to-end sales analysis project investigating key business metrics like KPI trends, hourly peak times, and sales distribution. Built with SQL and interactive Power BI.
SQL
Power BI
Data Cleaning
Excel
Data Modelling
DAX
Python
NumPy
Pandas
n8n Flows
Git & GitHub
Docker
I am actively seeking Data Analyst positions or BI dashboard-focused contract roles. If you have an interesting data pipeline problem or simply want to connect, feel free to reach out.
