We are seeking a skilled and self-motivated Data Engineer (intern) to strengthen our quantitative research and investment infrastructure. This project-based role focuses on rapidly designing, building, and optimizing data pipelines and systems that serve data-intensive and research-driven investment workflows. The ideal candidate will work closely with quant teams to ensure seamless data access and high-quality delivery under a defined timeline.
Key Responsibilities:
- Design, develop, and optimize scalable data pipelines to ingest, process, and store large volumes of structured and unstructured data from diverse sources, including daily market data and securities fundamental data.
- Build efficient ETL (Extract, Transform, Load) workflows to ensure data accuracy and readiness for quantitative modeling and back-testing.
- Collaborate with quantamental teams to translate data needs into robust, maintainable data solutions, with clear documentation and high reusability.
- Maintain and enhance data infrastructure, including databases, data lakes, and cloud-based storage solutions, to support high-performance analytics.
- Automate data validation, logging, and performance monitoring tools to ensure pipeline reliability with minimal manual intervention.
- Deliver project results on a tight timeline, with a focus on usability, stability, and scalability for long-term handover.
Requirements:
- Proven experience in data engineering, ideally within the financial services, quantitative research, or investment domains.
- Strong proficiency in Python and SQL, with practical experience using tools such as APScheduler, Airflow, Streamlit, Pandas, and NumPy.
- Hands-on experience with cloud platforms (e.g., AWS, GCP, or Azure).
- Strong problem-solving skills and the ability to work with large, complex datasets.
- Self-driven, collaborative, and able to thrive in a cross-functional, bilingual (English and Mandarin) environment.
If you are interested, please submit your resume to [Confidential Information] along with the following details:
- Your earliest availability date
- Your intended internship duration (preferably a minimum of 3 months 6 months or longer is ideal)
