Data Modeler – Finance

SCOR; Paris; Sur place; EUR 65 000 - 95 000; Plein temps

Résumé du poste

SCOR is seeking a Data Modeler for the Finance domain to join our Tech, Data & AI team. The successful candidate translates complex financial requirements into robust, scalable data models across systems to support reporting, closing, planning and decision-making.

You will design conceptual, logical and physical models, collaborate with Finance stakeholders, and ensure alignment with enterprise standards, data governance, and metadata management.

Qualifications

• Strong data modeling across conceptual, logical and physical layers.
• Experience in financial services with Finance data and processes.
• Experience building analytical data models for reporting and analytics.
• Proficiency in SQL and/or PySpark, with modern data platforms.
• Experience with Databricks and Palantir Foundry.
• Understanding of data governance, metadata management and data quality.
• Strong analytical thinking and attention to detail.
• Ability to collaborate with technical and business stakeholders.
• Excellent communication in an international, matrix environment.

Responsabilités

• Design, build, and maintain financial data models across the Data Foundation to support closing, planning and performance analysis.
• Develop analytical data models for scalable reporting and self-service analytics.
• Contribute to enterprise Finance data model with consistent definitions across domains.
• Collaborate with Data Engineers, Architects, and Finance stakeholders to reflect business semantics.
• Ensure data consistency, reconciliation capability, and proper handling of time dimensions and history.
• Support metadata management, glossaries, and data lineage with data stewards.
• Promote data modeling standards to improve quality and maintainability.
• Translate Finance requirements into robust data structures for operational and analytical needs.

Connaissances

Data modeling

Finance domain

SQL/PySpark

Databricks

Palantir Foundry

Data governance

Metadata management

Data quality

Stakeholder collaboration

Communication

Formation

MSc/PhD in data science

Outils

Databricks

Palantir Foundry

Description du poste

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.