ABOUT US:

From business process re-engineering to global business expansion for Japanese corporations, ABeam Consulting has served our clients through more than 40 years of growth. With our vision of being the No. 1 global consulting firm from Asia, ABeam Consulting helps our clients take on the challenge of business transformation. With 4,400 consultants in Japan, and 3,100 in overseas offices concentrated in Asia, our 7,500 consultants and global alliance partners provide truly comprehensive services.

Responsibilities:

• Collaborate with business stakeholders and technology teams to gather and analyze data requirements related to banking products, transactions, customers, and reporting.
• Design and maintain logical and physical data models for core banking, risk management, compliance, and financial reporting.
• Translate complex business use cases into normalized and de-normalized data structures optimized for both operational and analytical workloads.
• Implement and evolve data marts, data warehouses, and data integration layers aligned with the client’s data architecture.
• Work with development teams to deploy physical data models and optimize performance for large financial datasets.
• Ensure all data models comply with data governance, quality, and metadata management standards.
• Produce data documentation, including data dictionaries and lineage diagrams, for business, audit, and regulatory use.
• Support initiatives related to data lineage, metadata management, and data quality to enhance data trust and transparency.
• Provide business support with the ability to identify and highlight IT issues when necessary.
• Create and maintain reports and communicate effectively with both technical and business stakeholders.

Requirements:

• Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field.
• Min. 7–10 years of experience in data architecture, data modelling, or data management in the banking or financial services industry.
• Deep expertise in logical and physical data modelling, particularly for core banking, risk, compliance, and analytics use cases.
• Strong skills in data modelling tools such as Erwin, PowerDesigner, or similar.
• Advanced SQL skills with experience handling large, complex financial datasets.
• Solid understanding of relational and dimensional modelling, data warehousing, and integration techniques.
• Familiarity with data governance frameworks like DAMA-DMBOK.
• Intermediate understanding of APAC regulatory compliance.
• Excellent communication, collaboration, and documentation skills.
• Ability to create clear reports and work well in a team setting.
• Experience with the American data management platform Collibra (non-development role) is a plus.
• Good communication skills in both writing and spoken to communicate effectively with the stakeholders and clients.

• Collaborate with business stakeholders and technology teams to gather and analyze data requirements related to banking products, transactions, customers, and reporting.
• Design and maintain logical and physical data models for core banking, risk management, compliance, and financial reporting.
• Translate complex business use cases into normalized and de-normalized data structures optimized for both operational and analytical workloads.
• Implement and evolve data marts, data warehouses, and data integration layers aligned with the client’s data architecture.
• Work with development teams to deploy physical data models and optimize performance for large financial datasets.
• Ensure all data models comply with data governance, quality, and metadata management standards.
• Produce data documentation, including data dictionaries and lineage diagrams, for business, audit, and regulatory use.
• Support initiatives related to data lineage, metadata management, and data quality to enhance data trust and transparency.
• Provide business support with the ability to identify and highlight IT issues when necessary.
• Create and maintain reports and communicate effectively with both technical and business stakeholders