Build Scalable Paper-Trading Backend (Trading Engine) — Real-time Market Simulation -- 2
Budget: ₹50,000 – ₹500,000 INR
We are looking for an experienced backend developer (or small team) to build a paper-trading engine similar to Neostox, designed to handle ~20,000 concurrent users.
#Core Requirements#
Real-time market data ingestion (WebSocket/REST) → normalize tick-by-tick (Bid/Ask/Last/Volume/Timestamp).
Order Management System (OMS): Market, Limit, Stop, Stop-Limit, Cover/Bracket orders, multi-leg options.
Order execution simulation: fills, partial fills, latency/slippage simulation.
Account & Margin: balance, equity, margin used/free, realized/unrealized P&L.
Risk engine: enforce daily loss limit, max drawdown, auto-close on breach.
Instrument management: NSE F&O with auto weekly/monthly expiries, equities, indices.
APIs: REST + WebSocket endpoints for frontend integration (subscribe ticks, place/cancel/modify orders, account state, history).
Scalability: low-latency architecture (<100ms), designed for 20,000 users.
Stack (recommended): Core in C++/Go/Java, API layer in Python/Node.js/Java, DB PostgreSQL/TimescaleDB, Redis, Kafka/RabbitMQ, Docker + AWS deployment.
Monitoring: logs, metrics (Prometheus/Grafana).
#Deliverables#
Source code in Git repo (client-owned).
Deployment scripts (Docker).
API docs (OpenAPI/Swagger).
Database schema + architecture diagram.
Basic admin endpoints (user/instrument management).
Test reports (functional + load testing).
# Milestones (suggested)#
1. POC — Feed ingestion + single instrument injection.
2. Core OMS + API + account model.
3. Multi-instrument support + auto-expiry creation.
4. Load testing (simulate target users).
5. Documentation, deployment scripts, 30-day support.
#Important#
Clean, documented code is a must.
NDA + IP assignment required.
Previous experience with trading/finance systems preferred.
#Core Requirements#
Real-time market data ingestion (WebSocket/REST) → normalize tick-by-tick (Bid/Ask/Last/Volume/Timestamp).
Order Management System (OMS): Market, Limit, Stop, Stop-Limit, Cover/Bracket orders, multi-leg options.
Order execution simulation: fills, partial fills, latency/slippage simulation.
Account & Margin: balance, equity, margin used/free, realized/unrealized P&L.
Risk engine: enforce daily loss limit, max drawdown, auto-close on breach.
Instrument management: NSE F&O with auto weekly/monthly expiries, equities, indices.
APIs: REST + WebSocket endpoints for frontend integration (subscribe ticks, place/cancel/modify orders, account state, history).
Scalability: low-latency architecture (<100ms), designed for 20,000 users.
Stack (recommended): Core in C++/Go/Java, API layer in Python/Node.js/Java, DB PostgreSQL/TimescaleDB, Redis, Kafka/RabbitMQ, Docker + AWS deployment.
Monitoring: logs, metrics (Prometheus/Grafana).
#Deliverables#
Source code in Git repo (client-owned).
Deployment scripts (Docker).
API docs (OpenAPI/Swagger).
Database schema + architecture diagram.
Basic admin endpoints (user/instrument management).
Test reports (functional + load testing).
# Milestones (suggested)#
1. POC — Feed ingestion + single instrument injection.
2. Core OMS + API + account model.
3. Multi-instrument support + auto-expiry creation.
4. Load testing (simulate target users).
5. Documentation, deployment scripts, 30-day support.
#Important#
Clean, documented code is a must.
NDA + IP assignment required.
Previous experience with trading/finance systems preferred.