Data Engineer

Hedge Fund
New York, NY, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours

Tech stack

Query Performance Java (Programming Language) Bash Shell Big Data C++ (Programming Language) Computer Programming Data Infrastructure Data Systems Python (Programming Language) SQL Databases Data Storage Technologies Information Technology
+2 more
Data Analytics Api Design

Job description

Position Overview: Reporting to the Head of Data Analytics & Strategy, the Data Engineer will design, implement, and maintain complex data storage, pipeline, and analytics systems that support and further develop the data infrastructure of the organization’s Quantitative and Fundamental investment groups. Responsibilities include building large data pipelines and developing APIs to retrieve data, all to innovate the next level of analytics systems that effectively integrate with and enhance current research applications

Requirements

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  • 1-8 years’ relevant experience and a degree in Computer Science (or related field) with a strong GPA

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  • Strong foundational skills in SQL, query performance tuning, and bash/shell scripting

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  • Expert-level programming skills in Python and proficient with one of the following: Java/Scala, C/C++

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  • Expertise in data modeling and choosing an appropriate model given the situation

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  • Capital Markets and Asset Management experience and related datasets/vendors is a plus

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  • Ability to provide thought leadership and contribute to the firm’s overall technology strategy

Benefits & conditions

  • Work with researchers and portfolio managers to analyze and improve the architecture of or proprietary and derived data sets

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  • Solve interesting data engineering problems in support of quantitative researches leveraging time-series data

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  • Implement cloud data platforms capable of handling the computational complexities of machine learning workflows on large data sets

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  • Write code that provides reliable automated data pipelines, included automated quality checks

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  • Take ownership of the data engineering code base, focusing on high-quality delivery of both code and data

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  • Be a technical leader by building pipelines to explore and leverage alternative non-traditional data sources

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