Senior Python Engineer for Trading & Backtesting System Development

Job Title: Senior Python Software Engineer – Trading & Backtesting (Stocks & Crypto)

📍 Location: Remote / Hybrid (preferably within American time zones)

🕒 Type: Full-time – Contractor or Employee

💼 Level: Senior / Expert

🚀 About the Role
We are looking for a highly skilled Python Software Engineer to lead the development of a robust and scalable backtesting and automated trading system for both stocks and cryptocurrencies. You will be part of a strategic, high-impact project integrating historical data, real-time market APIs, and quantitative trading logic.

🔧 Responsibilities
Design and build a modular backtesting system supporting multiple asset classes (equities and crypto);
Develop and maintain real-time integrations with exchanges (Binance, Coinbase, etc.) And brokers (Interactive Brokers, Alpaca, etc.);
Build the core components of an automated trading system, including order execution, risk management, and performance tracking;
Work with market data (historical and live), data normalization, and financial time series processing;
Write unit/integration tests and ensure system reliability in production environments;
Collaborate closely with quants, analysts, and traders to translate trading strategies into efficient, scalable code.

🧠 Required Skills & Qualifications
Advanced proficiency in Python (5+ years of experience preferred);
Solid experience with pandas, numpy, and backtesting libraries like Backtrader, Zipline, or custom frameworks;
Strong knowledge of REST and WebSocket APIs for real-time data and order execution;
Deep understanding of financial data structures (OHLCV, order book, technical indicators);
Proven experience building backtest engines and analyzing performance metrics (Sharpe ratio, drawdown, etc.);
Comfortable with Git, ci/cd, and writing reliable, testable code using frameworks like pytest;
ability to work independently in a high-performance, low-latency environment.

🌟 Nice to Have
Experience with time series databases (InfluxDB, TimescaleDB, QuestDB, etc.);
Exposure to machine learning models applied to trading;
Familiarity with cloud platforms (aws, gcp) and containerized environments (docker, kubernetes);
experience deploying live trading systems in production;
understanding of slippage, latency, and market microstructure.

🎓 Education
Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related field;
A Master's or postgraduate degree in Quantitative Finance or Financial Engineering is a plus.

💬 Language Requirements
Portuguese: fluent
English: fluent reading and writing; speaking proficiency preferred

💰 Compensation
Competitive and aligned with senior-level market rates
Opportunity for performance-based bonuses or profit-sharing

If you're passionate about technology, markets, and want to work on real-world trading infrastructure at scale, we want to hear from you.