Company Overview:
Join a leading quantitative trading firm at the forefront of financial innovation. We apply cutting-edge technology and data science to drive market insights and trading strategies. As they continue to expand the tech-driven approach, we're looking for talented engineers with a background in file systems and storage platforms to help optimize and enhance our performance.
Role Overview:
As a C Engineer focused on File Systems and Storage Platforms, you will play a pivotal role in ensuring the reliability, scalability, and performance of our data infrastructure. You will be involved in architecting and developing highly efficient systems that handle large-scale, low-latency storage and data access, a key component in the high-frequency trading environment.
You will leverage your experience with C to design and optimize storage solutions, with a particular focus on managing real-time data feeds, distributed file systems, and high-performance computing environments. This is a fantastic opportunity for C engineers who want to break into the finance space, working with some of the brightest minds in quantitative trading.
Responsibilities:
- Develop and optimize C code to enhance the performance, reliability, and scalability of our file systems and storage platforms.
- Design and implement high-performance, low-latency storage solutions that handle large volumes of financial data.
- Work closely with trading and quantitative research teams to build solutions that support fast and efficient data access, retrieval, and processing.
- Implement real-time data feeds handling, ensuring that incoming market data is stored, indexed, and made available with minimal delay.
- Build and maintain distributed file systems and storage systems optimized for high-frequency trading environments.
- Write clean, efficient, and maintainable C code while adhering to industry best practices and performance benchmarks.
- Troubleshoot and optimize complex system performance bottlenecks, ensuring ultra-low latency and fault tolerance.
- Collaborate with cross-functional teams to design solutions for scaling systems and handling large-scale data workflows.
Key Qualifications:
- Bachelor's degree in Computer Science, Engineering, or related field.
- Extensive experience in C programming, with deep knowledge of advanced concepts (e.g., memory management, multithreading, low-level optimization).
- Strong background in file systems, storage platforms, and distributed systems.
- Proven experience working with high-performance computing environments, ideally involving real-time data storage and access.
- Experience with storage technologies such as databases, file systems (e.g., NFS, HDFS), and distributed storage frameworks.
- Knowledge of tools for performance profiling, benchmarking, and optimizing large-scale systems.
- Familiarity with modern C (C+ and beyond) and associated libraries.
- Passion for financial markets and a desire to apply engineering skills to solve complex problems in quantitative trading.
Preferred Qualifications:
- Experience working in or exposure to the financial services industry, particularly quantitative trading.
- Familiarity with high-frequency trading (HFT) systems and their associated challenges.
- Knowledge of multi-threading and concurrent programming, especially in a low-latency environment.
- Experience with cloud-based infrastructure or distributed systems frameworks.
How to Apply:
- Interested applicants are encouraged to submit their resume, highlighting relevant technical experience in C and storage platforms, as well as any personal projects or contributions to open-source technologies.