Case Study

Real Estate Marketplace Platform

Full-stack development for Brickbro — building a real estate marketplace from scratch across frontend, backend, and data workflows.

ProductionFull-Stack Development
View ContributionsStart a Project
  • NestJS
  • Next.js
  • TypeScript
  • Python
  • PostgreSQL
  • MongoDB
  • Google Maps API
  • Docker

Summary

Problem

A real estate marketplace had to be built from scratch — fast, reliable property search backed by solid data workflows.

Solution

Contributed across frontend and backend on a greenfield build — property search, data workflows, and a clean backend structure.

Impact

Shipped a live marketplace with reliable data, a maintainable backend, and strong property discovery.

Role

As one of the full-stack developers, I worked across frontend and backend — property search, data workflows, and the backend behind them.

Project Story

From Figma designs to a production marketplace

How a real estate marketplace came together from scratch — frontend, backend, and search.

01 / 04

01

Greenfield Build

Starting from the product's Figma designs, the team built a marketplace where buyers and sellers could list, search, and discover properties.

  1. Figma
  2. Build
  3. Ship
02

Clean Backend

Built a clean backend structure from the start, so the team could ship features quickly and keep production stable.

  1. Structure
  2. Maintainable
  3. Stable
03

Data Workflows

Built out parts of the platform's data workflows for consistency and low operational friction.

  1. Ingest
  2. Process
  3. Consistency
04

Search Experience

Built frontend features, including property search and a map-based discovery experience.

  1. Frontend
  2. Search
  3. Discovery

Contributions

What I built

A high-level view of the areas I worked on.

Clean Backend Structure

Built a clean backend structure so features were easy and safe to ship as the product grew.

NestJSMaintainability

Data Workflows

Built out data processing workflows for consistency and low operational friction.

PythonData

Reliable Data Layer

Helped keep property and marketplace data dependable across the systems that store and serve it.

PostgreSQLMongoDB

Frontend Features

Built user-facing features for a smooth marketplace experience.

Next.jsReact

Map-Based Search

Integrated map and location features for property search, discovery, and filtering.

Google MapsSearch

Modern Stack

Built on a modern stack chosen for performance and long-term maintainability.

Modern stack

Engineering

Technical highlights

Stack

Technologies used

  • NestJS
  • Next.js
  • TypeScript
  • Python
  • PostgreSQL
  • MongoDB
  • Google Maps API
  • Docker

Takeaways

What this project demonstrates

This case study demonstrates experience with production-grade SaaS systems, complex backend workflows, third-party integrations, async processing, payment infrastructure, and scalable business logic.

Production backend engineering
Integration-heavy system design
Multi-tenant SaaS thinking
Payment and commerce workflows
Async worker architecture
Business logic modeling

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