Skills
Required
python
trading
management
latency
design
routing
websockets
monitoring
logging
reliability
transactions
rabbitmq
kafka
data
processing
security
compliance
logic
development
api
integration
rest
concurrency
database
postgresql
mongodb
redis
containerization
kubernetes
aws
stack
microservices
numpy
scipy
testing
strategies
visualization
strategy
analysis
metrics
engineering
Job
Description
We are seeking an experienced Python Backend Engineer to join our team in building high-performance, scalable backend systems for algorithmic trading. The ideal candidate will have strong expertise in developing exchange integrations, optimizing order management systems, and ensuring low-latency execution. Responsibilities Design and develop scalable backend systems for real-time trading applications. Build and optimize order management systems with smart order routing capabilities. Integrate multiple exchange APIs(REST, WebSockets, FIX protocol) for seamless connectivity. Develop high-performance execution engines with low-latency trade execution. Implement a real-time monitoring, logging, and alerting system to ensure reliability. Design fault-tolerant and distributed architectures for handling large-scale transactions. Work on message queues (RabbitMQ, Kafka) for efficient data processing. Ensure system security and compliance with financial industry standards. Collaborate with quant researchers and business teams to implement trading logic. Requirements Strong proficiency in Python (4+ years)with a focus on backend development. Expertise in API development and integration using REST, WebSockets, and FIX protocol. Experience with asynchronous programming(asyncio, aiohttp) for high-concurrency applications. Strong knowledge of database systems(MySQL, PostgreSQL, MongoDB, Redis, time-series databases). Proficiency in containerization and orchestration(Docker, Kubernetes, AWS). Experience with message queues(RabbitMQ, Kafka) for real-time data processing. Knowledge of monitoring tools(Prometheus, Grafana, ELK Stack) for system observability. Experience with scalable system design, microservices, and distributed architectures. Experience with real-time data processing and execution. Experience developing backtesting engines capable of processing millions of events per second. Understanding of rule-based trading engines supporting multiple indicators and event processing. Experience in data processing libraries: pandas, numpy, scipy, scikit-learn, and polars. Knowledge of parallel computing frameworks(Dask) for high-performance computation. Familiarity with automated testing frameworks for trading strategies and system components. Experience in data visualization tools for trading strategy analysis and performance metrics. Knowledge of quantitative trading strategies and algorithmic trading infrastructure. Contributions to open-source backend or data engineering projects. This job was posted by Shivangi Mathur from Unifynd. Show more Show less
