Data Analytics Engineer (Bank / Finance, BI / ETL / Data Modelling, 40-46K)
Summary
Designs and builds scalable BI/ETL pipelines and data models for financial clients, translating business needs into robust analytics solutions using Oracle/SQL Server and Power BI.
SW9018 |22 Jul 2026 Data Analytics Engineer (Bank / Finance, BI / ETL / Data Modelling, 40-46K)
- Translate business needs into scalable analytics models and ETL designs with cross-functional teams.
- Lead workshops to define requirements, align expectations, and resolve client inquiries.
- Design storage structures and reconciliation checks; standardize exception controls for easy troubleshooting.
- Author clear documentation for functional and non-functional solution requirements.
- Architect adaptable data models that support growth while minimizing change risk and costs.
- Evaluate new data sources using structured frameworks to assess integration impact.
- Resolve data discrepancies and convert business logic into scalable technical workflows.
- Bachelor’s degree in Computer Science, Data Engineering, Mathematics, Statistics, Business, or a related field.
- 5+ years in IT, including 2+ years in BI, data migration, or data warehouse pipelines, and 3+ years in Oracle or SQL Server development.
- Strong background in data modeling (Star/Snowflake), quality metrics, DDL/DML, and PL/SQL Stored Procedures.
- Hands-on experience modeling, deploying, and tuning Power BI and SSAS servers, including RLS and M scripting.
- Knowledge of Hadoop, Python, Java Spring Boot, Docker, or OCP is a plus.
- Fluent in written and spoken English and Chinese (Mandarin and Cantonese).
- Proactive problem solver with strong multitasking abilities.
- Benefits:
- 35-45K Depends on Experience
- 10-20 Days Annual Leave
- 5-day Work Week
- Friendly and Energetic Working Environment