Key Responsibilities
Data SME & Business Support
- Act as the go-to PIC for data-related queries from business users across banking domains (e.g. Retail, GB, Compliance, Risk, Finance etc.).
- Support business users in identifying the right data elements, datasets, and data products for their use cases.
- Explain data definitions, lineage, and usage in business-friendly terms.
- Resolve data queries by working across data platforms, products, and source systems.
Business Requirements & Data Mapping
- Elicit, analyse, and document data-focused business requirements.
- Translate business requirements into logical and physical data mappings, including:
- Source systems
- Tables and columns
- Data elements and attributes
- Work closely with Group Technology and data engineering teams to ensure accurate interpretation of requirements.
- Facilitate requirement walkthroughs, clarification sessions, and data deep-dives.
Business Glossary & Documentation
- Create and maintain business glossary definitions, data element descriptions, and domain terminology.
- Support alignment between business definitions and technical implementations.
- Ensure documentation is kept current and reusable across teams and initiatives.
Enterprise Data Platform & Product Support
- Provide SME support for enterprise data platforms and data products (e.g. DWH, Data Lakes, Feature Stores).
- Support data onboarding, enhancements, and consumption use cases.
- Assist with UAT planning and execution for data-related initiatives, including validation of data against business expectations.
- Support troubleshooting and resolution of data issues in collaboration with platform and engineering teams.
Stakeholder & Demand Management
- Act as a trusted interface between business units, GCDO, and Group Technology.
- Proactively manage data demand intake and prioritisation for assigned domains.
- Provide regular updates on requirement status, dependencies, and delivery risks.
- Support broader data demand and asset management initiatives under GCDO.
Key Initiatives Supported
- Enterprise Data Platform & SME Support (e.g. DWH, Data Lakes, Feature Stores)
- Data Asset & Demand Management (requirements, documentation, UAT support)
- Feature Store and data product enablement
- GenAI initiatives (data requirements, readiness, UAT support)
- Adoption of analytics and data tools (e.g. OAS, EDSP) across business units
Qualifications & Skills
Experience
- 5–7 years of experience as a Business Analyst or Data Business Analyst.
- Prior experience in banking or financial services is strongly preferred.
- Hands-on experience working with enterprise data platforms or analytics environments.
Technical & Data Skills
- Strong understanding of data concepts, including data models, datasets, and data lineage.
- Working knowledge of SQL for basic data exploration and validation.
- Experience mapping business requirements to systems, tables, and columns.
- Familiarity with data platforms and tools such as Power BI, OAS, Denodo, Feature Stores, or similar is an advantage.
Soft Skills
- Strong analytical and structured thinking.
- Ability to communicate complex data concepts to non-technical stakeholders.
- Comfortable acting as a central point of contact and owning data queries end-to-end.
- Detail-oriented, organised, and proactive.
- Able to work across multiple stakeholders in a matrixed environment.
Nice to Have
- Exposure to data governance, business glossary, or metadata management.
- Understanding of Agile / Scrum delivery models.
- Experience supporting regulatory or compliance-driven data use cases.
