Lead Data Architect (Investment Management) (Contract)

sggovterp; Singapore; On-site; SGD 150,000 - 190,000; Full time

Job summary

sggovterp is seeking a senior, hands-on Data Architect to own the data design of investment management platforms. You will define data sourcing, ingestion, structuring and governance across front, middle and back office, ensuring MAS standards and Whole of Government compliance.

You will join a four-person delivery team at project start, designing unified data layers for holdings, market data and unstructured content, and architecting the retrieval and reconciliation infrastructure to support

Responsibilities

• Design and develop data models for investment data domains, including security, positions, transactions, valuations and reporting.
• Define source-to-target data flows and mappings centering on SimCorp Dimension with data vendors and downstream analytics.
• Develop unstructured data models and the architecture for ingestion, processing, indexing and retrieval of research, news and content.
• Define governance, metadata, and data quality standards and ensure MAS and Whole of Government compliance.
• Lead design reviews and act as design authority for investment-data architecture.

Job description

[What the role is]

We are looking for a senior, hands-on Data Architect to own the data design of our investment management platforms. You will define how investment data is sourced and ingested from multiple systems, structured and integrated within the organisation, governed and made available across front, middle and back office. You will stay close to implementation by producing models and specifications, reviewing build quality, and providing technical leadership to the team's data specialists. The role must deliver solutions that meet MAS technology standards and applicable Whole of Government compliance requirements.

The role sits in a four-person delivery team set up to establish a unified investment data architecture that enables generative AI use cases. You will design and drive implementation of three unified data layers - portfolio holdings, structured market and economic data, and unstructured research, news and sell-side content - together with the reconciliation and retrieval infrastructure that supports specific use cases across the investment value chain. You will join at the start of the build phase, designing against a product vision and user stories.

[What you will be working on]

Data architecture and modelling

• Design and develop the conceptual, logical and physical data models for investment data domains: security and reference data, positions and holdings, transactions, valuations and pricing, performance, benchmarks, risk, compliance, accounting and client reporting.
• Define and govern golden-source, reference-data and master-data standards for instruments, parties, legal entities, accounts and portfolios, including identifier strategy, entity resolution, lifecycle states, schema versioning and change control.
• Produce implementation-ready artefacts: DDL, transformation and mapping specifications, interface contracts and data quality rules.
• Define the IBOR / ABOR data design and the reconciliation points between investment and accounting books of record, with end-to-end auditability.
• Define source-to-target data flows and mappings centred on SimCorp Dimension, covering market and reference data vendors, custodians, counterparties, and downstream reporting and analytics.

Unstructured data and retrieval architecture

• Develop the conceptual, logical and physical data models for unstructured investment-information domains, including sell-side and broker research, market commentary, news, internal analytics and knowledge assets.
• Define the architecture and standards for document ingestion, processing and indexing, ensuring that source context, document structure and temporal attributes are preserved.
• Define metadata, taxonomy and classification standards for unstructured content to support governance, discoverability and retrieval.
• Define the architecture and technical standards for the vector database and embedding lifecycle, including embedding model selection, index design, evaluation and retrieval optimisation, and guide the AI Engineer's implementation.
• Define the entity and metadata mappings that link unstructured content to portfolio holdings and trades, enabling relevant research and news to be retrieved against current exposures.
• Design hybrid retrieval orchestration spanning all three layers (vector similarity combined with keyword filtering and metadata ranking) to support near-real-time market surveillance.

Platform and integration

• Define integration patterns and interface standards for batch, API, messaging and event-driven exchange across the investment-data ecosystem.
• Shape the target data platform for analytics and reporting across on-premise RDBMS / data warehouse and cloud lakehouse, and guide the migration path between them.
• Evaluate technology and vendor options, weighing performance, resiliency, security, cost and operational complexity.
• Take part in platform upgrades, replatforming and data migration, owning data mapping, parallel runs, cutover, reconciliation and legacy decommissioning.

Governance, quality and control

• Develop the data-governance framework and accountable ownership model covering metadata, business and technical lineage, data quality, retention, and access rights.
• Ensure designs meet MAS technology standards and Whole of Government compliance requirements.
• Define data classification and access controls for sensitive investment data, applied consistently across all three layers including unstructured research content.
• Define source-data lineage and audit requirements for reconciliation outcomes and AI retrieval; work with the AI Engineer to ensure end-to-end traceability across data, retrieval, model and application logs.

Leadership and delivery

• Serve as the design authority for investment-data architecture, lead data design reviews, and steer change proposals through the MAS Architecture Review Committee to validate alignment with Enterprise Architecture standards.
• Partner with portfolio management, investment operations, risk, finance, compliance a