Opportunities

We want the industry’s best and brightest talent to call K-HAWK home. We look for smart, hard-working individuals who strive for excellence and uphold the highest ethical standards. We support our team through coaching and training, helping them build long-term careers with us. We expect our employees to be problem-solvers, rigorous thinkers, and exemplary citizens. 

  • About

    Utilize programming and statistical methods to manage models for forecasting, strategy selection, and portfolio construction. Use quantitative methods in financial engineering to develop algorithmic solutions, modeling, and visualization of complex data.

    Requirements

    • Proficiency with Python software

    • 1 year experience with computer programming in financial environment

    • MA in Applied Mathematics and Statistics

  • About

    Utilize programming and statistical methods to manage models for forecasting, strategy selection, and portfolio construction. Apply operational and programming methodologies to ensure strategies run efficiently with minimal errors.

    Requirements

    • Proficiency with Python software and quantitative methodologies.

    • 1 year experience with computer programming in financial environment

    • MA Mathematics and Statistics, or Computer Science

  • Role Overview
    We are seeking a Quant Data Engineer with deep expertise in ClickHouse to build and scale our core data infrastructure. This role is central to enabling low-latency analytics, robust data pipelines, and high-performance research and trading systems.
    You will work closely with portfolio managers, quantitative researchers, and engineers to ensure data is accurate, scalable, and accessible for real-time and historical analysis.

    Key Responsibilities
    Data Architecture & ClickHouse

    • Design, build, and maintain ClickHouse clusters for large-scale financial time-series data

    • Optimize schemas for high-performance analytical queries

    • Tune query performance, partitioning, and indexing strategies

    • Manage real-time and batch ingestion pipelines

    • Monitor and improve system performance and reliability

    Data Engineering & Pipelines

    • Develop robust ETL/ELT pipelines for market and alternative data

    • Process high-frequency datasets (tick, trades, order book)

    • Ensure data quality, validation, and consistency

    Quant & Trading Support

    • Partner with quantitative researchers to deliver structured datasets

    • Enable efficient backtesting and research workflows

    • Optimize data access for trading systems

    Systems & Performance

    • Ensure low-latency data availability

    • Implement monitoring, alerting, and fault tolerance

    • Continuously improve scalability and system reliability



    Required Qualifications

    • 4+ years experience in data engineering or related field

    • Strong hands-on experience with ClickHouse in production (required)

    • Advanced proficiency in Python and SQL

    • Experience with time-series data and high-volume data pipelines

    • Familiarity with Kafka (or similar), Airflow/Prefect, and cloud platforms (AWS/GCP/Azure)



    Preferred Qualifications

    • Experience in hedge funds, trading firms, or financial data platforms

    • Understanding of market microstructure and order book data

    • Experience optimizing analytical databases at scale

    • Exposure to low-latency or real-time systems

      Ideal Candidate

    • Deep expertise in analytical databases (especially ClickHouse)

    • Strong systems thinker focused on performance and scalability

    • Comfortable working with large, real-time datasets

    • Collaborative and able to work across quant, trading, and engineering teams
      Compensation

    • Competitive base salary

    • Performance-based bonus

    • Comprehensive benefits



    How to Apply
    Please submit:

    • Resume

    • Relevant project or GitHub work (if available)

    • Brief summary of your ClickHouse experience


      Note: Candidates must have hands-on experience deploying and optimizing ClickHouse in production environments.Item description