Finance Data Architect

This is not a traditional technical modeling role. We are looking for a professional who understands how Finance and Actuarial processes operate within a reinsurance company and can translate that understanding into a scalable, governed, and business-aligned data architecture and data models.

You will work at the intersection of Finance, Actuarial, Data, and Technology teams to define the future-state Finance data model and establish the semantic foundation that supports enterprise-wide decision making.

Required experience & competencies

• 5+ years of experience in Data Architecture, Information Architecture, Enterprise Data Modeling, or related disciplines.

• Strong experience within the insurance or reinsurance industry.

• Deep understanding of Finance and Actuarial data domains, including several of the following: IFRS 17, Solvency II, Technical Closing, Reserving, Financial Planning & Analysis, Performance Management, General Ledger, Accounting structures, Reinsurance contracts and treaty data

• Proven experience designing enterprise-scale conceptual and logical data models used across multiple business functions.

• Experience defining canonical data models, business semantics, and data standards.

• Strong understanding of Finance data lineage, reconciliation, controls, and data quality requirements.

• Ability to engage effectively with senior Finance, Actuarial, and Technology stakeholders.

• Excellent communication skills with the ability to bridge business and technical domains.

Required Education 

• Degree in computer or data science, software or computer engineering, applied math, physics, statistics, or a related field or equivalent experience

Key duties and responsibilities

Your mission will be to:

• Design and own the enterprise Finance data architecture and data model supporting Reserving, Closing, Performance Management, Investments, Treasury, and Financial Reporting.

• Define and evolve conceptual, logical data models within SCOR's Data Foundation.

• Establish common business definitions, semantics, and canonical data structures across Finance, Actuarial, Risk, and Corporate functions.

• Lead the design of the Finance Analytical Data Model, ensuring consistency, traceability, reconciliation capability, and alignment across source systems and business processes.

• Work closely with Finance, Actuarial, and Business stakeholders to translate complex reinsurance and finance requirements into scalable and reusable data structures.

• Ensure appropriate handling of granularity, historical tracking, time dimensions, accounting perspectives, and regulatory requirements.

• Drive alignment between operational data, analytical data products, reporting requirements, and AI-enabled use cases.

• Define standards and best practices for Finance data architecture, information modeling, metadata management, and data governance.

• Support enterprise initiatives related to IFRS 17, Solvency II, Technical Closing, Reserving, Planning, Forecasting, and Performance analytics.

• Partner with Data Engineers, Solution Architects, and Domain Leads to ensure consistent implementation of target-state data models across the Finance ecosystem.