Data Modeler - Insurance (Contract)

Morgan McKinley; Hong Kong Island; On-site; HKD 900,000 - 1,300,000; Full time

Job summary

Morgan McKinley in Hong Kong hires a Data Modeler for a 12-month transformation project in a multinational insurance group. You will lead data modeling across enterprise apps, translating business needs into robust conceptual, logical, and physical models.

You will develop lakehouse schemas for policy, claims, and billing domains, partner with analysts, and implement data quality and governance with Azure, AWS, and Databricks. Strong SQL, ER/Studio/Erwin, and stakeholder skills are essential.

Qualifications

• 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.

Responsibilities

• Lead data modeling initiatives across enterprise digital applications, translating requirements into robust data models.
• Develop normalized, dimensional, canonical, and lakehouse schemas for core insurance domains.
• Partner with analysts and SMEs to define data lineage, master data rules, and business glossary alignments.
• Collaborate with data engineering to implement models as lakehouse tables, databases, APIs, and streaming layers.
• Work with data governance to implement data quality, retention controls, and auditability metrics.
• Maintain model repositories, versioning, naming conventions, and architectural decision records.

Skills

Data modeling

Data architecture

Data warehousing

Data engineering

SQL skills

Cloud platforms

Stakeholder management

Education

Bachelor's degree in CS/IS

Tools

Erwin Data Modeler

ER/Studio

Job description

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.