Senior Manager (Enterprise Data Architect)-Information Technology, CEO's Office

Securities and Futures Commission; Hong Kong; Sur place; HKD 1 000 000 - 1 400 000; Plein temps

Résumé du poste

The Securities and Futures Commission seeks an experienced Enterprise Data Architect to shape its data foundation and define architecture to govern, integrate, share and use trusted data across the organisation.

The role translates the Data & AI strategy into a practical target architecture and roadmap spanning enterprise data platforms, information models, metadata, data quality and governance capabilities, with a hands-on approach to enable analytics, machine learning and AI-enabled regulation.

Qualifications

• 10+ years of experience in Data Architecture or related fields.
• Degree in CS/IS/Engineering/Data Science or related discipline.
• Proven experience designing enterprise-scale data platforms and architectures.
• Deep knowledge of information modelling, data domains, metadata management, data warehousing and data integration.
• Strong understanding of relational and non-relational technologies, APIs, ETL/ELT and modern data-engineering patterns.
• Experience establishing architecture principles, standards and governance processes.
• Good understanding of catalogue, lineage, quality, observability and governance tools.
• Experience designing secure and scalable data environments across cloud, on-premises and hybrid platforms.
• Exposure to analytics, machine learning, generative AI or related data-enabled technologies would be an advantage.
• Strong communication and stakeholder-management skills.
• Certifications such as TOGAF, CDMP or Microsoft Azure certifications would be an advantage.
• Experience in financial services, financial regulation or regulated environments would be an advantage.

Responsabilités

• Define and maintain the enterprise data architecture strategy, principles, standards and roadmap.
• Develop and govern the enterprise information model, data domain architecture and target-state data landscape.
• Establish architecture patterns for structured, semi-structured and unstructured data.
• Set standards for data modelling, integration, metadata, quality and lifecycle management.
• Ensure architecture decisions support regulatory objectives, business needs, governance requirements and enterprise technology strategy.
• Lead architecture design and evolution of enterprise data platforms, analytical environments, metadata services and integration capabilities.
• Ensure the enterprise data architecture provides a robust foundation for analytics, machine learning and AI-enabled regulation.
• Establish reusable patterns for data ingestion, transformation, APIs, data products and access.
• Design metadata, catalogue, lineage and data-quality capabilities that improve discoverability and trust.
• Evaluate emerging data and AI-enabling technologies based on business fit, security, resilience and cost effectiveness.
• Define architectural approaches for semantic models, reference data and governed knowledge sources that support analytics, search and AI-enabled use.
• Lead data architecture governance and provide architecture assurance for Data & AI initiatives.
• Partner with business divisions, infrastructure, Information Security and governance teams to ensure coherent end-to-end solutions.
• Guide engineers and delivery partners on architecture patterns and standards.
• Manage architecture risks, technical debt and lifecycle considerations.
• Maintain architecture documentation and communicate recommendations to governance forums.
• Establish architecture expectations for DataOps, automated data testing, observability, reconciliation, recovery and cost-efficient operation of enterprise data services.
• Build internal Data Architecture capability and ensure knowledge transfer from vendors and delivery partners.

Connaissances

Data Architecture

Enterprise Architecture

Solution Architecture

Data Modeling

Data Warehousing

APIs

ETL/ELT

Security & Governance

Stakeholder Management

TOGAF / Certifications

Formation

Bachelor’s or Master’s degree in CS/IS/Engineering/Data Science

Outils

Data catalog tools

Description du poste

Senior Manager (Enterprise Data Architect)-Information Technology, CEO's Office

The Securities and Futures Commission is seeking an experienced Enterprise Data Architect to shape its enterprise data foundation and establish the architecture through which trusted data can be governed, integrated, shared and used across the organisation.

The role will translate the SFC’s Data & AI strategy into a practical target architecture and roadmap spanning enterprise data platforms, information models, integration, metadata, data quality and governance capabilities.

This is a strategic and hands‑on architecture role for someone with deep data expertise who can establish durable foundations for analytics, machine learning, generative AI and a more data‑enabled regulator. Data architecture is the core requirement, while AI‑enabling architecture experience would be a strong advantage.

Duties & Responsibilities

Enterprise Data Strategy and Architecture

Define and maintain the SFC’s enterprise data architecture strategy, principles, standards and roadmap.

Develop and govern the enterprise information model, data domain architecture and target-state data landscape.

Establish architecture patterns for structured, semi-structured and unstructured data.

Set standards for data modelling, integration, metadata, quality and lifecycle management.

Ensure architecture decisions support regulatory objectives, business needs, governance requirements and enterprise technology strategy.

Data Platforms and AI Enablement

Lead architecture design and evolution of enterprise data platforms, analytical environments, metadata services and integration capabilities.

Ensure the enterprise data architecture provides a robust foundation for analytics, machine learning, generative AI and future data-driven capabilities.

Establish reusable patterns for data ingestion, transformation, APIs, data products and access.

Design metadata, catalogue, lineage and data-quality capabilities that improve discoverability and trust.

Evaluate emerging data and AI-enabling technologies based on business fit, security, resilience and cost effectiveness.

Define architectural approaches for semantic models, reference data and governed knowledge sources that support analytics, search and AI-enabled use.

Architecture Governance and Delivery

Lead data architecture governance and provide architecture assurance for Data & AI initiatives.

Partner with business divisions, infrastructure, Information Security and governance teams to ensure coherent end-to-end solutions.

Guide engineers and delivery partners on architecture patterns and standards.

Manage architecture risks, technical debt and lifecycle considerations.

Maintain architecture documentation and communicate recommendations to governance forums.

Establish architecture expectations for DataOps, automated data testing, observability, reconciliation, recovery and cost-efficient operation of enterprise data services.

Build internal Data Architecture capability and ensure knowledge transfer from vendors and delivery partners.

Requirements

10+ years of relevant experience in Data Architecture, Information Architecture, Enterprise Architecture, Solution Architecture or Data Engineering.

Bachelor’s degree or Master’s degree in computer science, information systems, engineering, data science or a related discipline.

Proven experience designing enterprise-scale data platforms and architectures.

Deep knowledge of enterprise information modelling, data domains, metadata management, data warehousing and data integration.

Strong understanding of relational and non-relational technologies, APIs, ETL/ELT and modern data-engineering patterns.

Experience establishing architecture principles, standards and governance processes.

Good understanding of catalogue, lineage, quality, observability and governance tools.

Experience designing secure and scalable data environments across cloud, on-premises and hybrid platforms.

Exposure to advanced analytics, machine learning, generative AI or related data-enabled technologies would be an advantage.

Strong communication and stakeholder-management skills.

Relevant professional certifications, such as TOGAF, CDMP or Microsoft Azure certifications, would be an advantage.

Experience in financial services, financial regulation, regulatory technology or another highly regulated environment would be an advantage.

We are an EQUAL OPPORTUNITY EMPLOYER.