Senior Full-Stack Engineer with 12+ years building trading platforms, fintech systems, and SaaS applications.

I spend most of my time in Java Spring Boot and React on the application side, and Python + Airflow + dbt on the data pipeline side. I've designed systems that handle sub-100ms order execution, process 87K+ market symbols in real-time, and serve thousands of active mobile users.

Based in Dallas–Fort Worth, TX · Open to remote

Languages

Backend & Frameworks

Frontend & Mobile

Data & Pipelines

Databases

Cloud & DevOps

Java · Spring Boot · Kafka · gRPC · MongoDB · Redis · Docker

Microservices system that fetches and serves OHLCV candle data from multiple crypto exchanges. Uses Kafka for async download pipelines, gRPC for inter-service communication, Redis caching, JWT auth, and Flyway migrations. Includes architecture diagrams and full API documentation.

Java · Spring Boot 3 · PostgreSQL · JPA · SOLID

A reference implementation of 16 enterprise design patterns (Strategy, Observer, Chain of Responsibility, Saga, etc.) built into a multi-tenant order and audit platform. Demonstrates SOLID principles, clean architecture, and Java best practices.

C# · .NET Core · AWS EKS · MSK (Kafka) · Terraform · DynamoDB

Enterprise-scale Order Management System designed for high-frequency crypto trading with sub-100ms latency. Deployed on AWS using EKS, MSK, and infrastructure-as-code with Terraform.

Python · ClickHouse · VectorBT · ML · Telegram Bot

AI-powered Telegram bot for crypto trading — built with a MEXC data pipeline, ClickHouse data warehouse, VectorBT backtesting engine, ML-based predictions, and agentic AI capabilities.

Next.js · TypeScript · Real-Time Data

Interactive financial dashboard rendering real-time market data with charting, watchlists, and portfolio analytics.

These aren't on GitHub (proprietary), but they shape how I think about engineering:

• EC Trading Platform — Distributed trading backend with Actor model (Proto.Actor), sub-100ms execution for institutional clients, compliance checks, and portfolio risk calculations
• ProTradingScans — Multi-threaded stock scanning engine covering 87K+ US and Australian symbols, 30+ filter criteria, 10+ technical indicators, MongoDB time-series optimization (45% faster queries)
• MarketAlertPro — Real-time alerting system integrating with Finnhub, Polygon, and Norgate APIs — maintained 99.9% uptime
• Incometrader & Ivy Dividends — React Native mobile apps shipped to App Store and Google Play, serving 5,000+ active users with real-time market data and subscription management
• ETL Pipelines — Python + Airflow + dbt pipelines transforming financial data from multiple APIs into PostgreSQL for analytics dashboards and backtesting

Fintech & Trading Systems    ████████████████████  12+ years
Microservices Architecture   ██████████████████░░  Production scale
Event-Driven Systems (Kafka) ████████████████░░░░  Real-time pipelines
Data Pipelines (ETL/ELT)     ██████████████░░░░░░  Airflow + dbt + Python
Mobile (React Native)        ████████████░░░░░░░░  Published apps (iOS + Android)
Cloud Infrastructure (AWS)   ████████████░░░░░░░░  EKS, RDS, S3, MSK

I care about building systems that actually hold up in production — not just pass a demo. That means thinking about retry logic before the happy path, understanding where your system will break at 10x load, and writing code that the next engineer can read without a Rosetta Stone.

Most of my career has been spent in fintech, where latency matters, data accuracy is non-negotiable, and downtime costs real money. That context shaped how I approach everything — from database schema design to Kafka consumer group tuning.

I'm always up for conversations about distributed systems, fintech architecture, or backend engineering challenges.

📫 [email protected] 🔗 linkedin.com/in/mohsinrasheed