Senior Data Engineer/ 資深數據工程師

We are seeking an experienced Data Engineer to build and maintain a robust data ecosystem that processes multiple datasets from various internal and external sources. This role is critical to ensuring the accuracy, stability, and scalability of our data infrastructure, which is essential for the firm’s investment operations. The candidate will work closely with researchers, traders, and technology teams to drive data-driven decision-making and enhance system performance. This role offers a unique opportunity to cultivate and develop top talent within the Data Team, collaborating closely with the CEO, data statisticians, and traders to build models from the ground up. As a key contributor to our data infrastructure, the Data Engineer will be responsible for designing, implementing, and optimizing robust data systems. We foster a culture of open problem-solving, encouraging a balance between intellectual depth and practical implementation to drive innovation and excellence. Roles/ Responsibilities: • Develop and maintain scalable data pipelines to ensure efficient and fault-tolerant data processing. • Manage data collection, storage, cleansing, and transformation to enhance data quality and usability. • Experience in developing ETL (Extract, Transform, Load) processes using C++ is a plus, along with proficiency in Python for maintenance. • Implement and optimize MLOps methodologies to support scalable and reliable machine learning infrastructure. • Test and integrate APIs to facilitate seamless data exchange across internal and external systems. • Collaborate cross-functionally with investment, research, and engineering teams to deliver efficient data solutions tailored to business needs. Required Skills: • 6+ years of experience as a Data Engineer. • Extensive expertise in data collection, storage, and cleaning, with a strong preference for candidates who have built data systems from the ground up. • Strong technical skills in SQL, NoSQL (MongoDB, Cassandra), Spark, Hadoop, Python, Airflow, ETL, Data Warehousing, and Cloud platforms (AWS/GCP/Azure). • Experience with Kubernetes (k8s) for deployment is preferred. Preferred Qualifications: • MS/BS in Computer Science or a related engineering field is preferred. • Working proficiency in English skills (oral and written) Other Requirement: • Resilient, proactive, and optimistic, with strong critical thinking skills. • Goal-oriented mindset, willing to put in the effort, and passionate about data research-related work. Interview Process (Process sequencing may be adjusted as appropriate) Resume selection –>Coding Assessment -> F2F or Google Meet Interview( Hiring team) –> HR Manager