The Lead Domain Architect, Enterprise Data & Information Architecture, is a senior role within Group IT Architecture responsible for establishing and evolving Great Eastern's enterprise data and information architecture foundation across Singapore, Malaysia, Indonesia, and other GE entities. The role will define target-state architecture, principles, standards, and guardrails for enterprise data, information models, data flows, data platforms, data integration, metadata, lineage, data quality, access control, privacy, and governance-by-design. It will help address data fragmentation, inconsistent definitions, duplicated data flows, unclear authoritative sources, and architectural debt across the enterprise technology landscape. Working closely with business stakeholders, Group Data, application teams, platform teams, Security, Risk, Compliance, and delivery teams, the role will translate business, regulatory, data governance, and technology needs into practical architecture direction and implementable solution patterns. This role is also expected to provide architecture leadership and coaching to solution architects, engineers, and delivery teams, helping to uplift data architecture maturity across Group IT. The successful candidate will play a key role in enabling trusted enterprise data for business operations, analytics, regulatory needs, digital platforms, and scalable AI adoption.
Enterprise Data & Information Architecture - Define and evolve enterprise data and information architecture across Great Eastern entities, aligned with business strategy, enterprise architecture direction, regulatory expectations, and technology modernisation priorities. •
- Establish enterprise-level data domain models, conceptual and logical information models, canonical data patterns, and common data definitions for key business entities.
- Define principles and architecture guardrails for authoritative sources, golden records, data ownership, data lifecycle, data sharing, and enterprise data reuse.
- Identify and address structural data architecture issues, including fragmented data stores, duplicated data flows, inconsistent definitions, unclear system-of-record ownership, and architectural debt. Data Platform, Integration & Flow Architecture
- Define target-state architecture and transition roadmaps for enterprise data platforms, data warehouses, data lakes/lakehouses, operational data stores, analytics platforms, and data services.
- Establish architecture patterns for batch, real-time, streaming, API-based, and event-driven data integration.
- Guide the design of data pipelines, data products, data services, and data consumption patterns to ensure scalability, resilience, security, reusability, and operational efficiency.
Partner with application, integration, cloud, infrastructure, security, and delivery teams to ensure data architecture is embedded consistently across solution designs.
Governance-by-Design
- Translate data governance, privacy, security, risk, compliance, and regulatory requirements into practical architecture standards, controls, and design patterns.
- Define architecture standards for metadata, lineage, data quality, access control, data classification, retention, auditability, and observability.
- Work with business stakeholders, Group Data, Risk, Compliance, and Security to ensure governance requirements are built into systems, platforms, data flows, and delivery practices.
Support the establishment of trusted, governed, and reusable enterprise data assets for reporting, analytics, operational decisioning, and AI adoption.
Architecture Assurance & Delivery Guidance
- Provide architecture assurance for major programmes and initiatives involving data platforms, data integration, reporting, analytics, regulatory data, operational data, and AI-ready data foundations.
- Review solution designs to ensure alignment with enterprise data architecture principles, approved patterns, security standards, and governance requirements.
- Identify architecture risks, design gaps, technical debt, and remediation actions across data-related initiatives.
Serve as a key member of the Architecture Review Board for data and information architecture matters.
Leadership, Collaboration & Capability Building
- Provide architecture leadership, coaching, and mentoring to solution architects, engineers, data specialists, and delivery teams.
- Build reusable architecture playbooks, reference architectures, patterns, and decision frameworks to uplift data architecture maturity across Group IT.
- Influence stakeholders across business and technology teams to drive adoption of enterprise data architecture standards and target-state roadmaps.
- Champion practical, outcome-driven architecture that enables business value while managing technology, security, regulatory, and operational risks.
- Have strong experience in enterprise data architecture, information architecture, data management, or similar senior architecture roles within complex enterprise environments.
- Have a proven ability to define target-state data architecture, information models, architecture principles, standards, reusable patterns, and transition roadmaps.
- Understand how to structure enterprise data domains, business entities, canonical data models, authoritative sources, golden records, data ownership, and data lifecycle principles.
- Have practical experience with modern data platforms and patterns, including data warehouses, data lakes/lakehouses, operational data stores, data integration, streaming, APIs, event-driven architecture, data products, and analytics platforms.
- Understand governance-by-design concepts, including metadata, lineage, data quality, data classification, access control, privacy, retention, auditability, and observability.
- Can translate business, regulatory, risk, security, and data governance requirements into practical architecture standards, platform controls, and solution design patterns.
- Have experience reviewing and guiding major technology initiatives involving data platforms, data integration, reporting, analytics, regulatory data, operational data, or enterprise data services.
- Are able to identify structural data issues such as duplication, inconsistent definitions, unclear system-of-record ownership, unmanaged data flows, poor lineage, weak data quality controls, and architectural debt.
- Can work effectively with business stakeholders, Group Data, application teams, platform teams, Security, Risk, Compliance, and delivery teams to drive alignment and practical outcomes.
- Have strong communication, stakeholder management, influencing, and facilitation skills, with the ability to explain complex data architecture issues to both technical and non-technical audiences.
- Are able to provide leadership, coaching, and mentoring to architects, engineers, and delivery teams to uplift data architecture capability.
- Have strong analytical thinking, problem-solving capability, ownership mindset, and willingness to drive change in a complex enterprise environment.
- Have a bachelor's degree in Computer Sc
ience, Information Systems, Data Engineering, Data Management, or a related field, or equivalent practical experience.
- Have working knowledge of enterprise architecture frameworks, data management frameworks, or industry practices such as TOGAF, DAMA-DMBOK, DCAM, or equivalent. Have experience in insurance, banking, or financial services, which would be an advantage
