Data & AI Architect
- Singapore
- Lead/Staff
- 10+ years
- Posted
Skills
Required
- AI
- enterprise/solution architecture
- data/AI architectures
- streaming
- batch
- lakehouse
- analytics
- ML / GenAI
- enterprise data platform modernisation
- MLOps
- multi‑cloud or hybrid environments
- Azure
- Synapse / Fabric
- BigQuery / Vertex
- Kafka
Preferred
- CISSP / CCSP
- artificial intelligence
- Data & AI architecture
- data mesh/lakehouse
- domain roadmaps
About Ocbc
As Singapore’s longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932.
How?
- By taking the time to truly understand people.
- From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.
- Today, we’re on a journey of transformation.
- Leveraging technology and creativity to become a future-ready learning organisation.
- But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia’s leading financial services partner for a sustainable future.
- We invite you to build the bank of the future.
- Innovate the way we deliver financial services.
- Work in friendly, supportive teams.
- Or simply enjoy a vibrant, future-ready career.
- Your Opportunity Starts Here.
Responsibilities
- 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 target state and deliver business outcomes aligned to the enterprise architecture roadmap.
- 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.
- Chair/participate in design reviews for initiatives on Data & AI domain which span across channels, core banking, risk, finance, and compliance; adjudicate architecture decisions and manage dispensations with clear remediation timelines.
- 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.
- 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.
- Embed data quality, lineage, retention, encryption, and access controls.
- Ensure designs meet data privacy, model risk, and operational resilience requirements across jurisdictions.
- 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.
- Coach solution architects and engineers; curate reusable reference implementations and run patterns guilds to uplift Data & AI architecture competency across the organisation.
Requirements
- & 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 (e.g., 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.
Preferred
- TOGAF or equivalent.
- Azure Solutions Architect Expert; Azure Data Engineer or AI Engineer (or AWS/GCP equivalents); Databricks Professional; SnowPro; DAMA CDMP.
- CISSP/CCSP or equivalent; data privacy certifications are advantageous.
Benefits
- Build lasting value in your community.
- Help people grow their assets, business, and investments.
- Take your learning as far as you can.
- Competitive base salary.
- A suite of holistic, flexible benefits to suit every lifestyle.
- Community initiatives.
- Industry-leading learning and professional development opportunities.
- Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.
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