Engineer, Market Data

Engineer, Market Data

Posted Today

Balyasny Asset Management (BAM) is a diversified global investment firm founded in 2001 by Dmitry Balyasny, Scott Schroeder, and Taylor O'Malley. With over $32 billion in assets under management, BAM employs more than 2,000 people across 23 offices in the U.S. and Canada, Europe, the Middle East, and Asia. The firm’s investment teams span five strategies, including Equities Long/Short, Fixed Income & Macro, Commodities, Multi-Asset Arbitrage, and Systematic. Balyasny’s mission is to deliver to its investors absolute, uncorrelated returns in all market environments.

Role Overview

We are seeking a highly motivated, detail-oriented C++ Market Data Engineer to join our Market Data team. You will help design and build the firm’s central real-time market data distribution platform, a core resource requiring access at scale from many users and teams. The ideal candidate has deep experience developing high-performance feed handlers for both vendor (e.g., Refinitiv, Bloomberg) and direct exchange connections and is comfortable working in both C++ and Python to deliver robust, scalable solutions.

You will work closely with infrastructure, trading, and technology teams to ensure the platform is reliable, scalable, and meets the needs of systematic and discretionary strategies across all asset classes.

Key Responsibilities

• Design, develop, and optimize a high-performance, low-latency market data distribution system supporting large-scale access across the firm.
• Build and maintain feed handlers for direct exchange connections (e.g., NYSE, NASDAQ, CME, Eurex) and vendor data sources (e.g., Refinitiv, Bloomberg B-Pipe).
• Implement robust data validation, monitoring, and quality assurance processes.
• Develop and maintain APIs and data pipelines in Python to facilitate integration and analytics.
• Collaborate with infrastructure and DevOps to ensure performance, scalability, reliability, and security.
• Gather requirements, design solutions, and deliver production-ready systems in partnership with stakeholders and other engineering teams.
• Provide production support, troubleshooting, and timely resolution of issues.
• Contribute to architectural decisions and best practices for a central platform supporting large-scale usage.

Qualifications & Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 6+ years of hands-on software engineering experience, focused on real-time market data systems and distributed architectures.
• Expert-level proficiency in modern C++ (C++14/17/20) with a track record of building high-performance, low-latency systems.
• Extensive experience developing feed handlers for both vendor (Refinitiv, Bloomberg, etc.) and direct exchange protocols (e.g., FIX/FAST, ITCH, OUCH).
• Deep understanding of real-time data distribution models, network transport protocols (TCP, UDP, multicast), and messaging frameworks (e.g., Aeron, ZeroMQ, Kafka).
• AI-assisted development mindset: comfortable using AI tools to accelerate delivery while maintaining strong judgement around validation, refactoring, testing, security, and responsible usage.
• Experience building and supporting central platforms requiring access at scale from many users.
• Strong knowledge of market data types, symbol mapping/segmentation, and A/B arbitration.
• Expertise in memory management, threading/concurrency, CPU core affinity, and NUMA optimization.
• Proficiency in Python for APIs, data pipelines, and integration; Java experience is a plus.
• Strong verbal and written communication skills.
• Experience building centralized data platforms or services supporting large-scale internal usage.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Skills

• Experience with cloud-native architectures and containerization (e.g., Kubernetes, Docker).
• Familiarity with data serialization formats (e.g., SBE, Protobuf, Avro, FlatBuffers).
• Domain knowledge of Equities, FX, Futures, or Commodities is highly desirable.
• Experience with monitoring and observability for real-time systems (e.g., Prometheus, Grafana).