Data Modeler – P&C

We are seeking a Data Modeler for the P&C domain to join our Tech, Data & AI team. The successful candidate combines data modeling skills with a good understanding of (re)insurance processes. You bring the ability to translate functional requirements into structured, scalable, and business-aligned data models.

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

Key duties and responsibilities

Under the responsibility of the P&C Lead Data Engineer, your mission will be to:

• Design, build, and maintain conceptual, logical, and physical data models for P&C within the Data Foundation (Databricks & Palantir Foundry), supporting reinsurance processes such as underwriting, pricing, claims.
• Develop and evolve analytical data models that enable scalable reporting, self-service analytics, and AI-driven use cases.
• Contribute to the enterprise P&C data model, ensuring consistent business definitions and alignment across domains and systems
• Collaborate with Data Engineers, Architects, and P&C 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 P&C data.

Apply and promote data modeling standards and best practices to improve quality, reusability, and maintainability of P&C data assets

Required experience & competencies

• Experience in data modeling or data engineering, with a focus on understanding conceptual, logical, and physical models.
• Experience building analytical data models for reporting and analytics.
• Proficiency in SQL and/or PySpark, with understanding of modern data platform architectures.
• Experience in the insurance industry or in financial services is a strong plus.
• Experience with Databricks and/or Palantir Foundry is a plus.
• 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.