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.