Backend Engineer - Python

We are looking for a Python Backend Engineer to work on core backend systems for an algorithmic trading fund. The role involves building and operating services that process real-time data, integrate with external systems, and run continuously in production. This is a systems-focused engineering role where design quality, operational stability, and attention to detail matter. An understanding of financial markets can be a strong advantage, as it helps in reasoning about system behavior, edge cases, and reliability requirements in live environments.

Responsibilities:

• Design and develop backend services that process real-time and event-driven data.
• Build and maintain scalable data pipelines for ingestion, transformation, and downstream consumption.
• Develop internal services and APIs that support platform workflows and operational needs.
• Work on systems that integrate with external services and counterparties.
• Translate high-level logic and requirements into reliable, production-grade software.
• Build execution-critical services with a strong focus on correctness, observability, and fault tolerance.
• Implement safeguards and controls within backend workflows to ensure predictable behavior.
• Design systems that scale with increasing data volumes and account complexity.
• Monitor, maintain, and improve production systems, including incident response and post-incident fixes.
• Collaborate closely with engineering, research, and operations teams to evolve the platform.

Requirements:

• Strong proficiency in Python with experience building backend systems.
• Experience working with real-time or event-driven architectures.
• Solid understanding of asynchronous programming and concurrency.
• Experience building and integrating APIs (REST, WebSockets, or similar).
• Strong database fundamentals across relational and non-relational systems.
• Familiarity with message queues or streaming systems (Kafka, RabbitMQ, or similar).
• Experience designing systems for reliability, observability, and long-running production workloads.
• Comfort working in containerized and cloud-based environments.