Data Modeler – Finance
Summary
Designs and maintains financial data models in Databricks and Palantir Foundry to support reporting, closing, planning, and analytics for a reinsurance company.
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.
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.
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