Job Description

Your future team

Join our team as Data Modeler to design, develop, and maintain high-quality data models for leading financial institutions that support enterprise data warehousing, business intelligence, analytics, and regulatory reporting. The Data Modeler will be responsible for creating conceptual and logical, and support in the creation of technical data models, ensuring alignment with business requirements, data governance standards, and enterprise architecture.

The ideal candidate will possess strong expertise in banking data domains and be familiar with regulatory reporting frameworks, including AnaCredit, FINREP, and COREP, as well as broader regulatory expectations such as BCBS 239. The Data Modeler will collaborate closely with business stakeholders, regulatory reporting teams, data architects, and IT delivery teams to ensure that data structures accurately reflect business concepts and support high-quality, auditable reporting.

The advantages of joining us

• Career growth, your way
  Access top-notch training and career development, with a clear progression path to help you level up at your own pace.
• Global impact, local connections
  Work on international projects and collaborate with diverse teams, all while making an impact locally.
• Innovative work that matters
  Tackle cutting-edge projects and utilize the latest tech, with all the tools you need to stay ahead.
• Inclusive, flexible culture
  Embrace a culture where your voice matters, with flexible hours to balance work and life seamlessly.
• Purpose-driven work
  Get involved in sustainability initiatives and community service, making a real difference while growing your career.

How you’ll contribute to our success

• Conceptual Data Modeling
  • Develop enterprise-level conceptual data models representing key banking domains, including Customers and counterparties, Credit facilities and exposures, Deposits and accounts, Financial instruments and securities, Collateral and guarantees, Risk and capital metrics, General ledger and accounting, etc.
  • Facilitate workshops with business stakeholders to capture business concepts, definitions, and relationships.
  • Align conceptual models with the enterprise data strategy and business glossary.
  • Ensure consistency of terminology across Risk, Finance, and Regulatory functions.
• Logical Data Modeling
  • Translate conceptual models into detailed logical data models
  • Ensure traceability from business requirements to logical structures.
  • Align models with regulatory data dictionaries and industry standards, such as the Banks’ Integrated Reporting Dictionary (BIRD).
• Physical Data Modeling Support
  • Provide guidance and validation for physical data models implemented in Enterprise Data Warehouses or lakehouse environments.
  • Collaborate with data architects and engineers to define table structures and storage strategies, indexing and partitioning, data lineage and auditability.
  • Support implementation across different technologies
• Regulatory Reporting Enablement
  • Design data structures supporting regulatory reporting (e.g.: AnaCredit, FINREP, COREP, etc.)
  • Ensure alignment with EBA/ECB taxonomies.
  • Collaborate with Risk and Finance teams to interpret regulatory requirements and translate them into data model specifications.
  • Support data reconciliation between finance, risk, and regulatory datasets.
  • Contribute to compliance with BCBS 239 principles, ensuring data accuracy, completeness, consistency, and traceability.
• Data Warehouse & Analytics Modeling
  • Design data models for Enterprise Data Warehouses and data marts supporting risk, finance, and customer analytics.
  • Apply appropriate modeling methodologies
  • Ensure models support historization, auditability, and regulatory traceability.
• Data Governance & Quality
  • Align data models with data governance frameworks and metadata management practices.
  • Define and document critical data elements (CDEs) and support data quality rule definition.
  • Ensure compliance with data privacy and security regulations, including GDPR.
  • Contribute to data lineage and impact analysis documentation.
• Stakeholder Engagement
  • Collaborate with business teams including Risk and Finance departments, Regulatory reporting teams, data architects and engineers, Data governance and quality teams, and other business analysts and subject matter experts.
  • Lead data modeling workshops and present models to both technical and non-technical stakeholders.
  • Provide expert advisory on banking data structures and regulatory implications.
• Documentation & Standards
  • Produce and maintain comprehensive documentation, including:
    • Conceptual, logical, and physical data models
    • Data dictionaries and metadata
    • Source-to-target mappings
    • Lineage and impact assessments
  • Establish and enforce data modeling standards, naming conventions, and best practices.

Your Profile

• Master’s degree in Computer Science, Information Systems, Finance, Data Management, or a related field.
• 4+ years of experience in data modeling within the banking or financial services industry.
• Proven experience designing or supporting in the design of Enterprise Data Warehouse models.
• Demonstrated expertise in regulatory reporting, including AnaCredit, FINREP, COREP
• Experience working on BCBS 239 or similar regulatory compliance initiatives.
• Good understanding of different Data Modeling Methodologies (Entity-Relationship (ER) modeling, Third Normal Form (3NF), Dimensional Modeling (Star/Snowflake), etc.)
• Solid understanding of key banking domains
• Proficiency with data modeling tools such as: Erwin, ER/Studio, PowerDesigner, etc.
• Strong SQL skills and experience with relational databases.
• Understanding of ETL/ELT processes and data integration.
• Familiarity with data catalog and governance tools (e.g., Collibra, Alation, Informatica).
• Excellent analytical and problem-solving skills.
• Strong communication and stakeholder management abilities.
• Ability to translate complex regulatory requirements into structured data models.
• High attention to detail and data accuracy.
• Capability to work effectively in cross-functional and international teams.
• Solution-oriented mindset.
• Eager to learn, you maintain positive attitude and resilience
• Fluency in English and French

Interested? Please submit your resume in English

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