Asset Management Data Modeller,




Office Address

Project Description

As an experienced Data Modeller supporting our Asset Management group, we want you to bring your experience and best practice data modelling principles to the project teams you will work with. You will be working closely with Data Architect and strong network of solution designers and engineers to continue the build-out of our technical data strategy.


    • work closely with Data Architects and various system stakeholders to develop and maintain data models (conceptual, logical, physical and canonical) and definitions across all lines of business
    • advise and implement best practice data modelling production, storage, and consumption standards
    • maintain the glossary / data dictionary
    • be involved in project initiatives to drive alignment to our data principles and standards
    • build and maintain strong relationships with our key architects and stakeholders
    • understand and document how data is, or will be used, and its implications on people, processes, products and technology
    • implement appropriate data modelling governance framework
    • coordinate activities with the Enterprise Data Management team, working together with Enterprise Data Architects.


Must have

    • 2+ years in FinTech
    • understanding of data modelling principles
    • experience in developing both logical and physical data models
    • data analysis and mining skills
    • strong analytical skills
    • ability to translate business requirements to technical requirements
    • ability to translate high level design into specific implementation steps.

Nice to have

    • ability to manage multiple projects in parallel
    • proven track record in consulting, architecture, solutioning and implementation
    • understanding of emerging technologies, and their associated impact on enterprise environments.


English: C1 Advanced

English: B2 Upper Intermediate

Relocation package

If needed, we can help you with relocation process. Click here for more details: see more details

Work Type

Data Science

Ref Number


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