Jobs at Q Systems

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Enterprise Data Engineer

New York, NY
Data Engineers are the architects of the next generation platforms that control how we interact with and consumes information. They own the entire data pipeline starting with how we ingest data from the outside world, through the transformation of data into actionable insights, and finally the interfaces and APIs that our analysts and portfolio managers use to monetize that information. Throughout that process our data engineers work closely with investment professionals and researchers to design systems that answer some of the most challenging questions in the hedge fund industry.
Enterprise Data Engineers build pipelines that support datasets used by all investment teams and strategies across the company. They manage the firm’s most critical data sets and focus on applying software development best practices to solve complex data challenges. The expectation is that the data engineer has sound programming skills, strong business acumen, and a strong interest in finance.
Key Responsibilities
  • Develop solutions that enable internal analysts to efficiently extract insights from data. This includes owning the ingestion (web scrapes, S3/FTP sync, bespoke processes), transformations (Python, Perl) and interface (API, schema design, events, etc.)
  • Build tooling and automation around data pipelines that improve the efficiency, quality and resiliency of our data platform
  • Partner with internal analysts, quants and data scientists to design, develop, test and deploy solutions that answer fundamental questions about financial markets.
  • Take on an entrepreneurial mentality by building and selling your own ideas. We work in an evolving space and we expect you to help design our evolution by challenging the status quo and independently identifying opportunities to improve the entire data organization.
Required Skills
  • A passion for working with data and developing software to address data processing challenges
  • Proficiency with Python, C++, Java or equivalent
  • Proficiency with RDBMS, NoSQL, distributed compute platforms such as Spark, Dask or Hadoop
  • Prior experience building data pipelines from structured or unstructured data preferably including web crawlers
  • Prior work developing BI tooling and/or application development for data analytics
  • Advanced technical communication skills
  • Working knowledge of statistics, predictive analytics or machine learning techniques
  • Strong business acumen with prior experience in investment research or direct exposure to product or data science teams AND passionate about using data for investment decisions
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