Banking Data Architect - BIAN and Data Governance

Banking Data Architect – BIAN and Data Governance

Dicetek LLC is seeking an experienced Banking Data Architect to define enterprise and domain-level data architecture for a large-scale core banking transformation programme in Abu Dhabi, United Arab Emirates. The role focuses on developing consistent banking data models, establishing data governance controls and aligning API and event data structures with Banking Industry Architecture Network (BIAN) information concepts where appropriate. The successful candidate will bring extensive banking data architecture experience, with expertise in Master Data Management (MDM), canonical data modelling, banking domain models, metadata management, data lineage and data quality.

A key responsibility is defining customer, account, product, transaction and party data models while supporting customer master integration and consistent information exchange across banking platforms. The position also involves applying governed AI-assisted tools to data modelling, mapping, metadata discovery and quality analysis, ensuring that AI-generated outputs remain subject to appropriate governance and validation controls.

Location:

Abu Dhabi, United Arab Emirates

Country:
United Arab Emirates

City:
Abu Dhabi

Industry: Banking

Function:
Database Development-Administration

Salary:
Not disclosed

Gender: No Preference

Candidate Nationality:
Not specified

Job Type: Full Time

Work Arrangement:
On-site

• Define data architecture principles supporting the core banking transformation programme.
• Develop and maintain banking domain data models.
• Establish consistent definitions and relationships for critical banking data entities.
• Define customer, account, product, transaction and party data models.
• Support alignment between enterprise data architecture and banking domain requirements.
• Establish canonical and domain-specific data models.
• Provide architectural guidance on data structures and information exchange across banking systems.

• Apply BIAN information concepts to relevant banking data architecture decisions.
• Align banking domain models with appropriate BIAN semantics.
• Support consistency between banking data entities and service-domain information requirements.
• Define relationships between domain data models and integration interfaces.
• Review API and event payload structures for alignment with relevant BIAN information concepts.
• Promote consistent banking data definitions across relevant platforms and services.

• Define data architecture standards for API payloads.
• Establish consistent event schema structures supporting banking integration requirements.
• Align API and event data representations with relevant canonical and domain models.
• Review information structures used across banking service interfaces.
• Identify inconsistencies in data definitions and mappings.
• Support reusable and clearly documented data structures for integration services.
• Coordinate data modelling requirements with relevant architecture and integration stakeholders.

• Define data architecture considerations for Master Data Management.
• Guide integration of customer master data across relevant banking systems.
• Support consistent representation of customer and party information.
• Establish data modelling guidance for master data integration.
• Identify dependencies affecting the consistency of shared banking data.
• Coordinate relevant data architecture decisions across banking domains.
• Support alignment between MDM integration and established data governance requirements.

• Establish data ownership principles for relevant banking data domains.
• Defi…