Q/Kdb+ Software Engineer - Austin, United States - realsolutionpartners

    realsolutionpartners
    realsolutionpartners Austin, United States

    1 month ago

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    Description
    The Q/Kdb+ Software Engineer will be responsible for implementing, supporting, and maintaining Q/kdb+ Systems for a large government agency.

    The candidate will be working in an AGILE team framework and will be responsible for creating interfaces with Real Time kdb+ database to provide data for T+0 TCA reports, managing releases and code deployment for the system used globally, and working with Kx customers on hardware/software issues related to kdb+.


    Responsibilities:


    Develop and implement processes and procedures for the build-out and management of Kx system platforms, utilizing technical skills in Q/Kdb+, UNIX/Linux, Matlab, SQL, Perforce, Perl, Python, HTML, CSS, and XML.

    Create daily data loaders to transfer data files from different servers into the client's databases.
    Automate business user workflow based on user requirements.
    Train and advise the client's workers application in development and best practices; Kx and market surveillance.
    Perform ad hoc analysis on business and system solutions.

    Requirements:
    5+ years of hands-on development experience with KDB+/Q.
    Extensive experience with C#, Java, and Python.
    Hands-on experience with Linux/Unix and scripting languages.
    Strong knowledge of Capital Markets, especially in the Securities and Equities industry.
    Bachelor's degree in Computer Science, Information Technology, Engineering, or related field.

    Preferred Qualifications:
    Expertise in engineering relevant solutions using Kdb+/Q on systems of considerable scale and complexity.
    Strong computer science fundamentals and deep software development experience in Python, R, C++, or Java.
    Advanced Linux system knowledge.
    Exposure to electronic trading systems and/or real-time financial data management and analytics.

    Demonstrated ability to collaborate effectively with quantitative researchers or traders to understand their needs and design and engineer scalable, robust solutions.

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