Data Modeler – Finance

We are seeking a Data Modeler for the Finance domain to join our Tech, Data & AI team. The successful candidate combines strong data modeling expertise with a solid understanding of Finance processes in a reinsurance context. You bring the ability to translate complex financial requirements into structured, scalable, and business-aligned data models.

This position goes beyond pure technical modeling: it requires ownership of how Finance data is represented across systems, ensuring consistency, traceability, and alignment with enterprise standards to support reporting, closing, planning, and decision-making.

Responsibilities

Key duties and responsibilities

Under the responsibility of the Finance Lead Data Engineer, your mission will be to:

• Design, build, and maintain conceptual, logical, and physical data models for Finance within the Data Foundation (Databricks & Palantir Foundry), supporting financial processes such as closing, planning, and performance analysis.
• Develop and evolve analytical data models that enable scalable reporting, self-service analytics, and AI-driven use cases.
• Contribute to the enterprise Finance data model, ensuring consistent business definitions and alignment across domains and systems.
• Collaborate with Data Engineers, Architects, and Finance stakeholders to ensure models reflect business semantics and integrate into the overall data architecture.
• Ensure data consistency, reconciliation capability, and proper handling of granularity, time dimensions, and historical tracking in financial datasets.
• Support metadata management, business glossaries, and data lineage in collaboration with data stewards to provide transparent and governed Finance data.
• Apply and promote data modeling standards and best practices to improve quality, reusability, and maintainability of Finance data assets.
• Translate complex Finance requirements into robust and scalable data structures that support both operational and analytical needs.

Qualifications

Required experience & competencies

• Strong experience in data modeling, including conceptual, logical, and physical models.
• Proven experience in financial services, with a solid understanding of Finance data and processes.
• Experience building analytical data models for reporting and analytics.
• Proficiency in SQL and/or PySpark, with understanding of modern data platform architectures.
• Experience with Databricks and/or Palantir Foundry.
• Understanding of data governance, metadata management, and data quality principles.
• Strong analytical thinking, attention to detail, and ability to structure complex topics.
• Ability to collaborate effectively with both technical and business stakeholders.
• Excellent communication skills and ability to operate in an international, matrix environment.

Required Education

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

SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.