As a Data Analyst within the Data Strategy & Architecture team, you will collaborate with business users and technology teams to gather data requirements and support the design and development of logical data models and data marts. Your role will be essential in ensuring that data assets are structured effectively to facilitate business analytics and informed decision-making.

Job Responsibilities

• Partner with business stakeholders and technology teams to gather data requirements relating to banking products, transactions, customers, reporting, and analytics.
• Assist in the design and maintenance of logical and physical data models that reflect core banking operations and meet regulatory and financial reporting needs.
• Help translate complex business use cases into normalized and de-normalized data structures optimized for operational and analytical workloads.
• Support the implementation and evolution of data marts, data warehouses, and integration layers aligned with banking architecture.
• Collaborate with development teams on the deployment of physical data models and assist in performance optimization for large financial datasets.
• Ensure that data models adhere to data governance, data quality, and metadata management standards across banking domains.
• Contribute to the development of data architecture documentation, data dictionaries, and lineage diagrams for regulatory, audit, and business usage.
• Support data lineage, metadata management, and data quality initiatives to enhance trust and transparency in data usage.

Job Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field (Master's degree preferred).
• 2-4 years of experience in data analysis, data modeling, or data management, preferably in the banking or financial services industry.
• Basic knowledge of data governance principles (e.g., DAMA-DMBOK) is a plus.
• Familiar with logical and physical data modeling concepts, particularly in banking, risk, compliance, and financial reporting domains.
• Proficiency in data modeling tools (e.g., Erwin, PowerDesigner, or similar) is preferred but not required.
• Strong SQL skills and the ability to work with large, complex financial datasets.
• Understanding of relational and dimensional modeling, data warehousing, and data integration techniques.
• Basic knowledge of regulatory compliance in the APAC region is a plus.
• Good collaboration, communication, and documentation skills to engage effectively with both business and technical stakeholders.