This role is accountable for producing the end-to-end data flow maps, data lineage documentation and data landscape views that underpin Programme Bedrock and the wider One APAC Data Strategy. The Business Data Architect will kick-start Programme Bedrock pre-work: translating the consolidated business data requirements (2,600+ prioritized data fields across markets) into a validated, product-level view of what data exists at source, what flows into each country Data Lake (staging, conformed and consumption zones) and what is missing and must be hydrated.

The role sits at the intersection of business (Underwriting, Claims, Distribution, Reinsurance, Actuarial, Finance), Data & Analytics, Data Engineering and Market IT. Where the Data & Analytics Engineering (DAE) architects own the infrastructure and platform architecture, this role owns the business view of data: how critical data items originate in market core systems (e.g. Premia, Liberty Pro, iLiberty, Genesys and legacy C&S sources), how they move across systems and jurisdictions into the Data Lakehouse, and how they map to the LII APAC Product Hierarchy down to profit-centre level. Success in this role depends on strong stakeholder management – working hand-in-hand with the Data Foundation Lead, Data & Analytics Programme Manager, Data Engineers, Local Market IT and Regional and Market business stakeholders to produce data flow maps that are accurate, validated and decision-ready.

Key Responsibilities

Data Flow Mapping & Lineage (Programme Bedrock Context)

Design and produce end-to-end data flow maps for critical data items – from market source/core systems, through Data Lake staging, zone 2 and consumption zone 3, to downstream reporting, dashboards and analytics use cases.
Document data lineage and transformations for critical data elements identified in the Bedrock Master Data Requirements exercise, ensuring traceability that is audit-defensible and supports regulatory, governance and AI-readiness needs.
Map data availability by country/Data Lake against the LII APAC Product Hierarchy (to profit-centre level), building the consolidated Commercial Data Landscape view of what exists, where it sits (source only, staging, or consumption) and what is not captured at all.
Document cross-system dependencies and cross-border data flows, flagging data residency, privacy and regulatory considerations to the appropriate governance forums.

Data Inventory, Data Model Alignment & Gap Analysis

Own and mature the data asset inventory, catalogue and data dictionary aligned to the consolidated Master Data Requirements Template – resolving Not Specified, TBD and validation required availability statuses through structured validation with Market IT and Data Engineering.
Align business data requirements to the conceptual and logical data model of the target Data Lakehouse, ensuring the dependency between data model design and lineage tracking of critical data items is explicitly documented.
Perform gap and hydration analysis by market and product, quantifying the scale of data that must be brought into the Data Lakes and providing sizing input to the Data Foundation Lead, DAE architects and Data Engineering delivery plans.
Contribute to the Data Consolidation Plan towards a single source of truth, including recommended sequencing based on business priority (Top 200 fields, Horizon 1–3 priorities).

Stakeholder Engagement & Workshops

Work hand-in-hand with the Data Foundation Lead, Data & Analytics Programme Manager, Data Engineers, DAE/infrastructure architects, Local Market IT and Business stakeholders (Regional and Market) as the connective tissue between business data needs and technical implementation.
Plan and facilitate structured interviews and cross-functional validation workshops with business, technology and data stakeholders to corroborate actual operating data flows against documented processes – establishing a fact-based, evidence-backed view rather than relying on documentation alone.
Translate ambiguous business asks into clear data definitions, mapping rules and acceptance criteria that Data Engineering can build against, and play back findings to senior stakeholders in clear, visual, decision-oriented formats.
Manage competing priorities across multiple markets with tact, keeping momentum in an environment of constrained capacity and differing local system landscapes.

Governance, Ownership & Documentation

Produce and maintain the Data Ownership & Accountability Matrix – mapping data owners, stewards and custodians per data asset and highlighting ownership gaps for remediation.
Classify data assets by sensitivity and business function, aligning to Data Protection Policy, PDPA and applicable regulatory expectations (e.g. MAS guidelines) in partnership with Risk & Compliance.
Ensure all data flow maps, lineage records and inventory artefacts are version-controlled, audit-ready and handed over cleanly into BAU data governance processes.
Produce source to Datalake mapping document and data catalogue for missing data elements to complete Datalake hydration

Experience & Qualification Requirements

8+ years experience in data architecture and modelling, data business analysis or information architecture roles, with at least:
3+ years documenting data flows, lineage or data landscapes across multi-system / multi-market environments.
Experience in Insurance or Financial Services, ideally within data foundation, data lake or data governance programmes.
Demonstrated delivery of data inventory / data mapping / current-state data landscape assessments involving both business and IT stakeholders.
Relevant certification (e.g. DAMA CDMP, TOGAF, cloud data platform certifications) preferred.

Business Data Architect (12-month contract)