Senior Data Analyst-Enterprise Data Modeller
Summary
Designs and builds enterprise-scale data models for banking systems, translating regulatory and business needs into standardized structures for risk, reporting, and analytics.
Required Experience and Skills
- 6–8 years of enterprise data modelling experience, preferably within banking or financial services.
- Strong hands-on experience developing conceptual, logical,and physical data models.
- Demonstrated experience modelling data within finance, risk,regulatory reporting, or related banking domains.
- Strong understanding of banking data structures, business concepts, and data relationships.
- Experience working with enterprise data modelling tools; ER/Studio experience is highly desirable.
- Exposure to industry-standard banking or financial services data models and the ability to adapt industry models to enterprise requirements.
- Experience supporting regulatory reporting and translating regulatory or reporting requirements into data models.
- Knowledge of enterprise data architecture, data governance, metadata management, data lineage, and data quality principles.
- Ability to analyse complex source systems and datasets and translate them into standardised enterprise models.
- Strong stakeholder management and communication skills, with the ability to work effectively across business and technology teams.
- Experience working in large, complex, global organizations and across geographically distributed teams.
Preferred Qualifications
- Experience with banking regulatory reporting frameworks, including exposure to MAS610.
- Experience establishing or implementing enterprise-wide data modelling standards and governance.
- Experience with Silver-layer, curated, canonical, or enterprise data models within modern data platforms.
- Familiarity with data warehouse, data lake, lakehouse, and analytical data architectures.
- Exposure to large-scale banking data transformation or regulatory change programmes.
- Experience contributing to global data architecture or data management initiatives.
Key Competencies
- Enterprise and strategic thinking
- Strong analytical and data modelling capability
- Banking, finance, and risk domain knowledge
- Attention to detail and data quality
- Stakeholder engagement and facilitation
- Ability to simplify complex data requirements
- Strong documentation and governance discipline
- Collaborative approach across global and cross-functional teams