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Data Modeler – Finance

Open 25d reposted 2× · 2 open copies

Summary

Designs and maintains financial data models for a reinsurance company, translating complex finance processes into scalable structures using Databricks and Palantir Foundry to support reporting and analytics.

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

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