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Company Overview
A leading financial institution in Singapore, established in 1932, is on a journey of transformation to become Asia’s leading financial services partner for a sustainable future. The organization leverages technology and creativity to deliver innovative solutions, support career growth, and create lasting value for clients and communities.
Role Purpose
Lead the enterprise data and artificial intelligence (AI) architecture strategy and blueprints that govern how data is collected, secured, processed, activated, and monetised across the bank. Act as design authority across programmes to ensure solution designs conform to the target state and deliver business outcomes aligned with the enterprise architecture roadmap.
Key Accountabilities
Enterprise Blueprints & Roadmaps: Define and maintain the target-state Data & AI architecture (e.g., data mesh/lakehouse, streaming, analytics, MLOps, metadata/lineage) and domain roadmaps aligned to business strategy and regulatory obligations
Cross‑Domain Design Authority: Chair or participate in design reviews for initiatives on the Data & AI domain spanning channels, core banking, risk, finance, and compliance; adjudicate architecture decisions and manage dispensations with clear remediation timelines
Standards, Patterns & Reference Architectures: Publish and evolve standards for data modelling, eventing, ML lifecycle, feature stores, model risk controls, privacy-by-design, and responsible AI; drive adoption through architecture governance gates
Solution Guidance & Quality Assurance: Partner with solution architects and engineering leads to shape designs (batch/stream, APIs, real-time scoring, vector stores/RAG, feature pipelines) and assure conformance to blueprint pre-build, during build, and pre-go-live
Risk, Controls & Compliance: Embed data quality, lineage, retention, encryption, and access controls; ensure designs meet data privacy, model risk, and operational resilience requirements across jurisdictions
Value Realisation & Metrics: Define measurable outcomes (e.g., time-to-model, reuse of data products/patterns, cost-to-serve) and track via OKRs; inform investment prioritisation through architecture insights
People & Capability: Coach solution architects and engineers; curate reusable reference implementations and run patterns guilds to uplift Data & AI architecture competency across the organisation
Experience & Competencies
10–15+ years in enterprise/solution architecture, with at least 6 years leading data/AI architectures at scale (streaming, batch, lakehouse, analytics, ML/GenAI)
Proven ownership of enterprise data platform modernisation and MLOps across multi-cloud or hybrid environments
Strong grasp of data governance, lineage/metadata, model risk controls, and responsible AI practices, including privacy and security-by-design
Hands-on expertise with major cloud data/AI platforms (Azure Synapse/Fabric/ML, AWS Redshift/SageMaker, GCP BigQuery/Vertex AI), streaming (Kafka), orchestration, catalog/lineage tools
Excellent stakeholder management and communication across business, technology, risk, and compliance; able to influence senior leaders and arbitrate design decisions
Demonstrated ability to define new architectures, lead cross-domain programs, and drive adoption of standards and patterns with measurable outcomes
Expected Certifications (nice-to-have)
Architecture: TOGAF or equivalent
Cloud/Data/AI: Azure Solutions Architect Expert; Azure Data Engineer or AI Engineer (or AWS/GCP equivalents); Databricks Professional; SnowPro; DAMA CDMP
Security/Privacy: CISSP/CCSP or equivalent; data privacy certifications are advantageous
Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore.
1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality. 2. No Client Relationship: This company is not a client of SpringCube unless stated. 3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job. 4. No Liability: SpringCube is not liable for inaccuracies.
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