Job Description

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

• 5+ years of 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.

Behavioral & Management Skills :

• 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.