Data Engineer - Hedge Fund (HK or SG based)

The Data Engineer will collaborate with stakeholders to create scalable data solutions for hedge fund operations, ensuring data quality through automation. Key responsibilities include integrating vendor data, contributing to platform development, and mentoring junior engineers. Candidates should have a strong technical background in cloud platforms, SQL, Python, and data orchestration tools, along with at least 5 years of experience in finance. Effective communication and an understanding of fi

Options Group (Hong Kong) - Hong Kong - Full time

Salary: HKD 1,000,000 per annum

 

Data Engineer (HK or SG based)

Key Responsibilities:

  • Customer-Focused Data Solutions:
    Work closely with clients to identify their unique requirements, converting them into effective, scalable data solutions tailored for hedge fund operations. This involves integrating new financial data sets, creating data pipelines, and establishing external connections, along with implementing automated testing early in the development cycle.

  • Data Quality Automation:
    Design and implement automated data quality checks throughout the development and data lifecycle. Ensure the integrity, reliability, and quality of data, while developing monitoring systems that enable the DataOps team to swiftly address issues with minimal disruption.

  • Vendor and Platform Integration:
    Oversee the integration of data feeds from external vendors, ensuring quick onboarding and thorough data validation. Collaborate with internal systems related to trade management, risk assessment, and the firms central Data Platform.

  • Platform Development Contributions:
    Analyze customer needs to identify patterns and recommend configurable frameworks. Ensure that process telemetry data is in place to monitor and address potential performance bottlenecks.

  • Promote Continuous Improvement:
    Uphold high standards of technical quality, responsibility, and customer service. Provide mentorship to junior engineers and assist in recruiting new talent. Enhance workflows and data quality to facilitate quicker insights and better decision-making for clients.

Qualifications & Experience:

  • Educational Background:
    Bachelors, Masters, or PhD in Computer Science, Physics, Engineering, or a related field.

  • Professional Experience:
    At least 5 years of experience in the financial sector, particularly in Front Office Technology or Quantitative roles, with a preference for candidates with hedge fund experience.

  • Technical Expertise:

    • Proficient with cloud platforms (AWS, Google Cloud, Azure) and associated data storage/processing services (e.g., AWS RDS, S3, MSK).
    • Strong Linux skills.
    • Advanced SQL expertise and experience with modern data storage/querying technologies (Snowflake, Redshift, BigQuery) and formats (Parquet, Iceberg).
    • Solid programming skills in Python and familiarity with Pandas; experience with high-performance coding in languages like C#, F#, C++, or Java is advantageous.
    • Background in test automation, preferably using DBT, to support high standards and rapid changes.
    • Knowledge of production monitoring with tools like Grafana, Prometheus, DataDog, or ELK.
    • Familiarity with data pipeline orchestration tools (e.g., Airflow) and data retrieval methods (e.g., sFTP, vendor APIs).
    • Experience with integrating third-party data sources and APIs typical in hedge funds.

  • Financial Data Acumen:
    Understanding of market and reference data, particularly across various asset classes, and familiarity with hedge fund data workflows, real-time data requirements, and financial compliance issues (licensing, access control).

  • Interpersonal Skills:
    Strong communication abilities with both Front Office stakeholders and technical teams, a collaborative spirit, curiosity, and the capability to thrive in an agile environment.

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