Senior Specialist Data Modeling

You are as unique as your background experience and point of view. Here youll be encouraged empowered and challenged to be your best self. Youll work with dynamic colleagues - experts in their fields - who are eager to share their knowledge with you. Your leaders will inspire and help you reach your potential and soar to new heights. Every day youll have new and exciting opportunities to make life brighter for our Clients - who are at the heart of everything we do. Discover how you can make a difference in the lives of individuals families and communities around the world.

Job Description:

Role Overview

We are seeking a highly skilled Data Modeler with strong expertise in Data Vault 2.0 Life Insurance domain Enterprise Data Warehouse design and Analytical/BI Reporting models (Star Schema).
The role will be end-to-end data modelling across complex multi-market implementations working closely with Business BAs BSA Data Engineers and KPI governance teams to design scalable governed and high-quality enterprise data models.

Key Responsibilities

1. Data Vault 2.0 Modelling (Atomic Layer)

• Own the design of Hubs Links Satellites PITs and Bridge constructs following DV 2.0 standards.
• Ensure proper business key identification hashing strategy and auditability.
• Review & guide junior modelers on DV patterns naming conventions and modelling best practices.

2. Life Insurance Domain Modelling

• Translate Life Insurance business processes (Policy Claim Premium Persistency Distribution Product Riders Benefits Channels Advisors etc.) into scalable data models.
• Understand KPIs such as AFYP APE NOP Persistency UW stages Claims metrics etc. and design data structures that support these KPIs.

3. Data Warehouse & Star Schema Design

• Create robust Dimensional Models including Facts Dimensions Hierarchies Slowly Changing Dimensions (SCDs).
• Ensure analytical models support self-service BI dashboards and regulatory reporting.
• Optimize models for performance consistency and scalability.

4. Requirements & Source-to-Target Mapping

• Work with BA/BSA and business SMEs to translate requirements into conceptual logical and physical models.
• Complex source system analysis especially for Life Insurance core systems (e.g. Ingenium Life Aisa CRM Other admin systems).

5. Stakeholder Collaboration

• Work closely with Engineering BA QA Product Owners and Governance teams.
• Present models and rationales to leadership and cross-market stakeholders.

6. Governance & Standards

• Enforce Data Vault 2.0 enterprise modelling standards and KPI governance frameworks.
• Own metadata lineage definitions naming conventions and documentation.

Required Skills & Experience

Technical Skills

• 46 years of overall experience in Enterprise Data Warehousing.
• 1 years hands-on experience in Data Vault 2.0 modelling (Hubs Links Satellites PIT Bridge).
• Expertise in Dimensional Modelling (Star Schema Fact/Dimension design).
• Knowledge of Life Insurance domain including products policy lifecycle claims distribution premium flows riders benefits persistency etc.
• Experience with ETL/ELT pipelines SQL and cloud DWH platforms (Snowflake / Azure / GCP / AWS optional).
• Understanding of BI Reporting structures for dashboards and KPI calculation.
• Expertise in metadata lineage data quality rules and data governance.

Soft Skills

• Strong analytical thinking and problem-solving ability.
• Excellent communication and ability to explain models to technical & non-technical stakeholders.
• Leadership mentoring and team-coordination skills.
• Ability to work in multi-market cross-functional environments.

Preferred Qualifications

• Certification in Data Vault 2.0 (CDVP2) is a strong advantage.
• Experience working in Life Insurance companies consulting firms or DWH modernization programs.
• Hands-on experience with modelling tools (Erwin ERStudio SQLDBM dbt etc.).

Why Join Us

• Work on enterprise-level DWH and KPI initiatives across multiple markets.
• Opportunity to shape the modelling strategy for large-scale Life Insurance datasets.
• Work with senior leaders and Asia-level data teams.
• High-visibility role with strong growth potential.

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