Data Engineer (FinTech) | HKD 40-70K
Summary
Senior Data Engineer for a fintech client (via David James Recruitment) in Kowloon: designs risk-control and growth analytics frameworks, fraud/anomaly detection models, BI dashboards, and end-to-end data pipelines using SQL, Python, Spark, Flink, Hive, ClickHouse, and Kafka, while leading and mentoring a data analytics team.
Our client is seeking an experienced Senior Data Engineer to lead data-driven decision-making, risk control analytics, and business growth strategies. You will design and execute core data indicator frameworks, big data analytics models, and risk management logic for high-volume transaction environments.
Responsibilities:
Framework & Indicator Design: Establish end-to-end data analysis frameworks across business growth, transaction quality, user behavior, fund flows, and risk management. Build metric tracking systems covering operational efficiency and anomaly detection.
Risk Modeling & Anomaly Detection: Design, test, and optimize big data models, real-time risk identification rules, and fraud/anomaly detection logic to prevent business risks and transactional threats.
Dashboards & Executive Reporting: Develop intuitive BI dashboards and daily/weekly executive risk alert reports to empower senior management and operational teams with actionable insights.
Data Pipeline Collaboration: Partner with data engineering teams to design, implement, and streamline end-to-end data pipelines across collection, cleaning, storage, processing, and analytical layers.
Team Leadership & Strategy: Lead, mentor, and grow a dedicated data analytics team. Build data analytics and risk control frameworks from scratch.
Requiements:
Education: Bachelor’s degree (or above) in Statistics, Data Science, Mathematics, Computer Science, or a related quantitative field.
Domain Expertise: Proven track record in big data analytics, risk control analytics, transaction analysis, or growth analytics. Prior experience in payments, fintech, transaction platforms, digital wallets, cross-border payments, or risk systems is strongly preferred.
Technical Proficiency:
Advanced SQL mastery for complex data extraction, cleaning, and multidimensional modeling.
Hands-on familiarity with modern big data technologies and frameworks (e.g., Python, Spark, Flink, Hive, ClickHouse, Kafka).
Experience designing and managing Data Warehouses, metric frameworks, BI dashboards, and real-time monitoring platforms.
How to Apply:
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