Data Modeler Consultant

About the Role:

We are seeking a Data Modeler Consultant with strong expertise in data modeling and enterprise data architecture to design and maintain unified data models that support Risk Management Services systems. This role requires hands-on experience in conceptual, logical, and physical data modeling, as well as experience working with modern data platforms and ETL processes. You will be responsible for developing scalable data models, documenting data flows and quality rules, and ensuring alignment between business processes and technical data structures across risk management and analytical data environments.

Responsibilities:

• Based on the documented Risk Management Services business process model, develop a unified contextual and logical data model for the in-house rebuild of the current EDS, RTSM, and RHC systems
• Review and expand the Risk Logical Data Model (LDM) to future-proof the solution design for Seller Risk Management under both ticket-based and order-based sales models
• Create and document the information flow model that describes how information moves through the system, characterizes relevant data inputs and outputs at different stages of the process, and captures the type or method of data access
• Contribute to the creation of technical design specifications, including source-to-target mapping documentation for ETL developers
• Document data quality requirements and validation rules, and identify commonly used data concepts (e.g., party, customer, product, agreement, transaction) to ensure alignment and sharing across the Financial Services portfolio
• Capture data analytics and reporting needs in support of Risk Management Services, and propose a data modeling approach for the FSDS analytical data warehouse
• Develop (or amend the existing) business data glossary that defines all business terms associated with the workflows and classifies the hierarchical structure of any aggregated or analyzed data concepts
• Ensure compliance with organizational standards and best practices

What we are looking for:

• Bachelor’s or master’s degree in computer/data science technical or related experience
• 5+ years of hands-on experience in data modelling principles/methods including conceptual, logical and physical data models
• Experience with modelling tools (such as Hackolade, ERWin and ER/Studio)
• Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-centre context
• Ability to synchronize models to ensure that database structures match business model(s)
• Experience with AWS architectures and implementations such as Kubernetes, Snowflake or Talend
• Ability to communicate effectively with both technical and non-technical audiences
• Fluent reading, writing and speaking abilities in English