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mohsinds/README.md

Hey, I'm Mohsin πŸ‘‹

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 Β· Open to remote


What I Work With

Languages

Backend & Frameworks

Frontend & Mobile

Data & Pipelines

Databases

Cloud & DevOps


Featured Projects

🏦 Candilize β€” Distributed Market Data Platform

Java Β· Spring Boot Β· Kafka Β· gRPC Β· MongoDB Β· Redis Β· 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.


🧩 Spring Boot Enterprise Patterns β€” 16 Design Patterns in Production Context

Java Β· Spring Boot 3 Β· PostgreSQL Β· JPA Β· 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.


⚑ Crypto OMS on AWS β€” Cloud-Native Order Management System

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


πŸ€– FM Analyzer Bot β€” AI-Powered Trading Intelligence

Python Β· ClickHouse Β· VectorBT Β· ML Β· Telegram Bot

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


πŸ“Š Market Dashboard (private / available on request)

Next.js Β· TypeScript Β· Real-Time Data

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


What I've Built in Production

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

  • EC Trading Platform β€” Distributed trading backend with Actor model (Proto.Actor), sub-100ms execution for institutional clients, compliance checks, and portfolio risk calculations
  • ProTradingScans β€” 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 β€” Real-time alerting system integrating with Finnhub, Polygon, and Norgate APIs β€” maintained 99.9% uptime
  • Incometrader & Ivy Dividends β€” 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 β€” Python + Airflow + dbt pipelines transforming financial data from multiple APIs into PostgreSQL for analytics dashboards and backtesting

Domain Expertise

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

How I Think About Engineering

I care about building systems that actually hold up in production β€” 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 β€” from database schema design to Kafka consumer group tuning.


Let's Connect

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

πŸ“« mohsin.mr@gmail.com πŸ”— linkedin.com/in/mohsinrasheed

Pinned Loading

  1. candilize candilize Public

    Candilize is a service for fetching and serving OHLCV (candle) market data from multiple crypto exchanges. It exposes REST APIs for candle data and is designed to evolve into a distributed system w…

    Java 1

  2. TDA_GUIv2 TDA_GUIv2 Public

    Forked from cjmiller81/TDA_GUIv2

    V2

    TypeScript

  3. cjmiller81/TDA_GUIv2 cjmiller81/TDA_GUIv2 Public

    V2

    TypeScript 2

  4. spring-boot-enterprise-patterns spring-boot-enterprise-patterns Public

    A comprehensive Spring Boot 3 application demonstrating enterprise architecture patterns, 16 design patterns, and a production-ready multi-tenant order & audit platform with SOLID principles and Ja…

    Java 1

  5. crypto-oms-aws crypto-oms-aws Public

    This is an enterprise-scale Order Management System (OMS) built on AWS, designed to handle high-frequency cryptocurrency trading with sub-100ms latency requirements. The system demonstrates modern …

    C#

  6. fmanalyzerbot fmanalyzerbot Public

    AI-powered Telegram bot for crypto trading: MEXC data pipeline, ClickHouse warehouse, VectorBT backtesting, ML predictions & agentic AI. Open-source fintech platform for algorithmic trading.

    Python


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