Senior Data Infrastructure Engineer (USA)

Posted 2 Days Ago
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Stamford, CT
Senior level
Machine Learning • Business Intelligence
The Role
The Senior Data Infrastructure Engineer will evaluate and enhance the company's data infrastructure to optimize the data pipeline for trading activities. Responsibilities include designing scalable solutions, monitoring performance, and collaborating with cross-functional teams to implement improvements and maintain efficient operations in financial trading environments.
Summary Generated by Built In

Description

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
Requirements
    • 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 are 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 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

Top Skills

Python
The Company
HQ: Stamford, CT
67 Employees
Hybrid Workplace
Year Founded: 2012

What We Do

Being a quantitative finance firm that uses Machine Learning (ML) to create multi-asset portfolios and seek profit from the market, Trexquant has continuously improved its investment and research platform since starting operations, leveraging new and emerging technologies. Trexquant uses rigorous quantitative methods to create multi-asset portfolios in global markets. To do this, Trexquant develops trading signals using its vast and continuously growing collection of data variables used as inputs for more complex trading models called Strategies. The result is an ever-growing and adapting engine built from thousands of intricate models and tens of thousands of signals, tailor-made with the goal to outperform the market during any condition. Capital is managed across 5,500+ cash equity positions across the United States, Europe, Japan, Australia, and Canada.

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