Senior Specialist - Data Modeling

Sun Life

22h

About The Position

You are as unique as your background, experience and point of view. Here, you’ll be encouraged, empowered and challenged to be your best self. You'll 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, you'll 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.

Requirements

• 4–6 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.
• 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.

Nice To Haves

• 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.).

Responsibilities

• 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.
• 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.
• 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.
• 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).
• Stakeholder Collaboration Work closely with Engineering, BA, QA, Product Owners, and Governance teams . Present models and rationales to leadership and cross-market stakeholders.
• Governance & Standards Enforce Data Vault 2.0, enterprise modelling standards, and KPI governance frameworks. Own metadata, lineage, definitions, naming conventions, and documentation.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1-10 employees