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Data Modeller and Architect Tokyo


9-18 Data Modeller and Architect/データモデラー&アーキテクト


Professional Services & Consulting

7-9 million
 The project is part of a regulatory requirement wherein data architecture need to be created for data concepts. These models would make the bank materially compliant to traceability and lineage requirement by banks.
1. Talk to Business and IT stakeholders and capture information related to various data concepts.
2. Create and maintain Conceptual and Logical data models, and data dictionary.
3. Conduct review meetings with Business and IT stakeholders in various functions.
4. Define and govern data modeling standards, tools, and best practices.
5. Analyze data flows between various systems.
6. Coordinate with IT SMEs to understand physical data (files, API, databases, etc.) and map it to the logical data model.
7. Create knowledge repository and perform 4 eye check of repository based on standards defined.
1. Fluent in Japanese and English languages.
2. Good understanding of trade lifecycle in an investment bank. Working knowledge of front office trade capture of one or more asset classes.
3. Expertise in data modeling principles and good understanding of either UML or Entity Modelling techniques.
4. Good working knowledge of a modeling tool such as Visio, ERWin or PowerDesigner.
5. Good technical knowledge of Excel and SQL.
6. Comfortable in analysis of large sets of data.
7. Expertise in business analysis techniques.
8. Methodical in approach and ability to break down a goal into tasks and execute.
9. Ability to clearly communicate complex technical ideas, regardless of the technical capacity of the audience.
10. Strong inter-personal skills and ability to work as part of a team.
Nice to have:
1. Working knowledge of concepts, terms and calculations in one or more areas: Financial Control, Liquidity or Risk Management.
2. Working knowledge of Reference data: Book, Entity, Instrument, Rating, Limit, etc.
3. Working knowledge of board reports: Leverage ratio, RWA, Revenue, Liquidity Coverage Ratio, etc.
4. Experience working with dimensionally modeled data.
5. Experience in translating/mapping relational data models into XML and Schemas.
6. Enterprise Architecture tool expertise.