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Salary
$20k – $86k per year (Estimated)
Location
In office (Mumbai)
Overview
Company
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Northstar Quant is a quantitative investment management firm that uses systematic, algorithmic trading strategies across Indian markets to offer market-neutral returns, research-driven trading, and risk management.

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.

Good to Have:

  • Understanding of financial markets, particularly exchange-traded products and derivatives.
  • Prior experience working on systems where correctness and uptime are critical.
  • Exposure to market data, execution systems, or risk-aware workflows (from a systems perspective).
  • Experience building internal platforms or tooling used by technical teams.
  • Familiarity with Golang in performance-sensitive components.
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