FinTech
Datachamps
Starting point
Started from an empty repository
Nothing was here before — I set up the repository and built the whole thing.
What I owned
- Designed
- Built
- Tested
- Shipped
- Operated
The moving parts
What talks to what — clients, services, data, and the boundaries between them.
Push to prod
The checks a change has to pass before it ships, and what watches it after.
Where it lives
The cloud it runs on — ingress, compute, data and messaging — and how that gets provisioned.
Node detail
Pick a box
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The product
Financial-analysis tool on PostgreSQL letting analysts explore data through dashboards, with a desktop companion app and automated report generation.
What I built
First production engagement. Joined a 4-person frontend team (myself, a backend developer, a project lead and a QA); after 3 months began covering backend as well, leaving a 3-person team — myself across both frontend and backend, the project lead and the QA. Delivered web application features with React and Node.js/Express on AWS, designed the REST APIs and PostgreSQL schemas, built the Electron bridge that connects the web app to its desktop companion, and automated Power BI reporting with Selenium scripts on an AWS Windows instance — replacing a manual process.
Everything I did here
- Joined a 4-person frontend team (myself, a backend developer, a project lead and a QA); after 3 months began covering backend too, leaving a 3-person team of myself (frontend and backend), the project lead and the QA.
- Built dashboards letting analysts explore financial data directly.
- Built the desktop companion app and the Electron bridge connecting it to the web app, so the dashboards can drive desktop-side capabilities.
- Automated Power BI report generation with Selenium scripts running on an AWS Windows instance, replacing the manual reporting process.
- Delivered production web application features with React, Node.js/Express and AWS.
- Designed REST APIs and database schemas on PostgreSQL.
- One of two engagements here built on PostgreSQL rather than MongoDB.