Trexquant is a growing systematic fund manager with a core team of highly accomplished technologists. We apply a wide variety of statistical and machine learning techniques to build investment portfolios and trade our client assets in global equity and futures markets. With locations in the US, China, and India, our global team in excess of 50 employees is comprised primarily of research professionals with advanced science, math, and technology degrees who explore the universe of quantitative methods for opportunities to enhance and adapt our platform and profit in an exciting and dynamic environment.
We are seeking a Senior Data Infrastructure Engineer to join our team. In this role you will be evaluating the company’s existing data infrastructure and proposing enhancements to streamline and optimize the data pipeline. You will design and implement scalable and reliable data infrastructure solutions that can accommodate the company’s growing data needs and trading volumes. This data pipeline supports the simulation and trading of a wide range of global financial assets, including equities, futures, and fixed income securities.
Responsibilities:
- Design and implement scalable and reliable data infrastructure solutions.
- Assess the current state of the company’s data infrastructure, including data storage, processing systems, and data pipelines.
- Identify bottlenecks, inefficiencies, and areas of improvement within the data infrastructure that hinder data processing and trading activities.
- Develop and propose solutions to optimize and streamline the data pipeline, leveraging the latest technologies and best practices in data engineering.
- Collaborate with cross-functional teams including data scientists, quantitative researchers, and software engineers to implement proposed enhancements to the data infrastructure.
- Monitor the performance of the data infrastructure and proactively address any issues or potential bottlenecks to ensure smooth operations.
- Keep up-to-date with the latest developments and trends in data engineering and financial technology to continuously improve the firm's data infrastructure.
Qualifications:
- BS/MS/PhD degree in Computer Science, Engineering, or other related field.
- 5+ years of experience in data engineering, including experience with data storage, processing, and pipeline technologies such as Hadoop, Spark, Kafka, and cloud-based data platforms (e.g., AWS, Azure, GCP).
- Strong programming skills in Python.
- Experience in Linux, shell/bash scripting, SQL, and/or C++ are a plus.
- Familiarity with financial markets and trading systems is a plus.
- Ability to analyze complex problems, propose innovative solutions, and implement them effectively within a fast-paced trading environment.
- Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.
- Demonstrate ability to drive initiatives from conception to implementation, with a focus on delivering high-quality solutions that meet business objectives.
Benefits:
- Competitive salary plus bonus based on individual and company performance.
- Collaborative, casual, and friendly work environment.
- PPO health, dental, and vision insurance premiums fully covered for you and your dependents.
- Pre-tax commuter benefits.
- Weekly company meals.