I turn complex financial and operational data into clear decisions, using SQL, Python, Power BI, Tableau, and seven years of fintech context behind every chart.
For more than seven years I worked inside fintech operations at a payment processor, helping a portfolio of 12,000+ merchants keep running: analyzing their transactional, billing, and settlement data across $50M+ in monthly volume, resolving discrepancies, and building the reports leadership relied on to make decisions.
That work made me want to understand the tools and processes behind it all more deeply, so I went back to school for a B.S. in Information Technology, expanding my technical foundation and learning how the systems I had worked with actually fit together.
Along the way I realized my real passion was in the data itself. I leaned all the way in, completing an intensive Data Analytics Bootcamp, building real-world projects in SQL, Python, Tableau, and Power BI, and preparing to begin an M.S. in Data Analytics. I continue sharpening my ability to turn messy data into clear decisions, a craft I plan to keep enriching for a long time.
The skills I use to collect, clean, analyze, and visualize data, and a toolkit I am always expanding.
Extracting, filtering, and aggregating data, from simple lookups to multi-table joins and complex subqueries.
Data cleaning, transformation, and analysis, from formulas and pivot tables to automated Power Query workflows.
Interactive dashboards and reports with calculated measures, data modeling, and visual storytelling.
Interactive dashboards, KPI tracking, and data storytelling that surface outliers at a glance.
Data manipulation and visualization through real projects using industry-standard libraries.
Shipping full-stack side projects, like a production platform on Supabase/PostgreSQL with REST APIs and an LLM chatbot.
Each project built around a real business question and real data.
How did lending to Myanmar shift across political periods, and where did cancelled projects land?
Analyzed World Bank IDA lending data across eras, sectors, and individual projects in MySQL, turning a broad geopolitical funding story into a structured, data-driven analysis of 11,171 records.
Read the case study → Also on LinkedIn ↗Interactive dashboard analyzing dropout patterns across 1,861 schools, identifying 37 critical schools and a strong relationship with economic disadvantage.
Read the case study → Tableau ↗Found income explains 67% of spending variation, and that discount-heavy campaigns underperform for high-value segments.
Read the case study → LinkedIn ↗End-to-end data platform tracking the global launch market (cadence, reliability, reuse, and mass to orbit) on a Databricks lakehouse with a dbt star schema.
Architecture overview → GitHub ↗Verified credentials across cloud, data, security, and IT. Click any badge to verify.
In progress: Microsoft Power BI Data Analyst (PL-300)
The things I enjoy most when I'm not working.
I love this sport for its blend of speed, strategy, and reading your opponent in real time. Proud registered member of USA Fencing.
Movies of every era, from brand-new releases to old classics. My all-time favorites: Top Gun and Drive.
Spaceships, space exploration, and honestly anything with the word "space" in it. It even sparked my AZIMUTH launch-analytics project.
I stepped out of the corporate world for a while to witness my first daughter's earliest milestones. I wouldn't trade it for anything.
Seeking Data Analyst and BI Analyst opportunities in Seattle or remote. If you're working in data or hiring, I'd love to hear from you.