About the Client
Our client is a prominent, multinational insurance group based in Hong Kong that is driving a large-scale digital and data transformation. They operate across multiple regional markets, building advanced cloud data platforms to enhance customer experience, enterprise analytics, and AI capabilities.
They are looking for a Data Modeler on 12 months contract basis for a transformation project.
Key Responsibilities
- Lead data modeling initiatives across the Group's enterprise digital applications, translating complex requirements into robust conceptual, logical, and physical data models.
- Develop normalized, dimensional, canonical, and lakehouse data schemas for core insurance domains including policy, customer, claims, actuarial, and financial processing.
- Partner with business analysts and SMEs to establish standardized definitions, data lineage, master data rules, and business glossary alignments.
- Collaborate closely with data engineering teams to convert approved models into lakehouse tables, database structures, APIs, and streaming event layers.
- Work alongside data governance and security teams to implement data quality rules, classifications, retention controls, and auditability metrics.
- Maintain model repositories, version controls, naming conventions, and architectural decision records across the organization.
Requirements
- Bachelor's degree in Computer Science, Information Systems, Data Management, or a related technical discipline.
- Minimum of 5 years of hands-on experience in data modeling, data architecture, data warehousing, or data engineering.
- Strong expertise in relational modeling, dimensional design, slowly changing dimensions, and modeling platforms such as erwin Data Modeler or ER/Studio.
- Solid background in the insurance industry, with deep knowledge of domains like policy, claims, product, reinsurance, or billing.
- Strong SQL skills for data profiling, with exposure to cloud platforms (Azure, AWS, Databricks, Delta Lake) and streaming structures (Kafka, Avro, JSON).
- Excellent analytical, facilitation, and stakeholder management skills, with the ability to articulate complex data concepts to both technical and non-technical teams.
