Data Architect at Momentum Metropolitan Holdings Limited

Role Purpose    

• The Data Architect is responsible for shaping and driving the organisation’s data strategy through the design, oversight, and enhancement of the enterprise data architecture. This role ensures all data initiatives, platforms, and models align with the Group’s broader data framework and strategic direction.
• The Data Architect plays a key role in translating business strategy into practical, scalable data capabilities. This includes influencing and educating stakeholders on data platforms, best practice usage, and the value of data-driven decision-making. The position oversees the implementation and monitoring of data-related work and projects to ensure adherence to architectural standards, governance practices, and long-term data capability maturity.

Requirements    

• Bachelor’s degree in Computer Science, Information Technology, or related field
• Advantageous: Certifications in data architecture, data management, cloud platforms, data analytics, machine learning, applied AI or enterprise architecture
• 5–7 years’ experience in data architecture, data modelling, data analytics, machine learning, applied AI or enterprise data management.
• Deep understanding and proven success of building data frameworks, embed data governance, metadata management, and creating and socialising master data principles.
• Strong proficiency with database technologies, data integration patterns, and modern data platforms (cloud/on prem)
• Experience with Azure, AWS or Google Cloud data services
• Ability to influence stakeholders and drive adoption of data practices
• Excellent analytical, conceptual, and problem-solving skills
• Strategic & technical AI/analytics leadership
• AI-driven opportunity identification
• AI & analytics capability roadmap shaping

Duties & Responsibilities    

Perspective: Strategy & Process

• Lead the development, evolution, and socialisation of the organisation’s data and AI architecture in alignment with the Group’s data strategy and enterprise data framework.
• Provide strategic input on how data and AI capabilities, platforms, and processes should evolve to support business strategy.
• Translate strategic objectives into tactical implementation plans for data and AI projects and data platform enhancements.
• Design, refine, and govern enterprise data and AI models, flows, and integration patterns that ensure consistency, scalability, and interoperability.
• Monitor and evaluate execution of data and AI related projects to ensure adherence to standards, architectural principles, and business value outcomes.
• Establish and maintain data and AI architecture standards, reference architectures, design patterns, and documentation.
• Identify opportunities to optimise data availability, data quality, and data usage across the organisation.
• Partner closely with data engineering, AI and BI teams to ensure smooth implementation of data solutions.

Perspective: Finance

• Ensure strategic data and AI decisions balance long term sustainability with cost effectiveness.
• Evaluate data platform and AI investments, ensuring alignment to architectural direction and maximum return on investment.
• Support financial and business analytics functions with accurate, well governed data structures and processes.
• Track and optimise the cost of storage, compute, and data movement across environments.

Perspective: Client Services / Stakeholder Engagement

• Influence, guide, and educate business stakeholders on data platform capabilities, AI opportunities, appropriate usage, and data-driven decision making.
• Act as the key advisor on data and AI implications of business initiatives, ensuring alignment with architectural principles and data governance requirements.
• Promote and embed a culture of responsible data usage and ownership across the business.
• Translate complex data and AI architecture concepts into clear, business-friendly language.
• Provide consultation and training to teams to uplift data and AI literacy and capability.

Perspective: People

• Foster an environment of cross-functional collaboration and shared accountability for data assets.
• Mentor and support team members involved in data and AI engineering, analytics, and data management.
• Promote continuous learning and professional development related to modern data and AI practices, tools, and frameworks.
• Encourage knowledge sharing to uplift organisational data and AI capability maturity.

Competencies    

Knowledge / Skills / Attributes

• Strong analytical, conceptual, and data modelling skills
• Strategic thinker with the ability to translate business goals into architectural direction
• Excellent communication, stakeholder management, and influencing skills
• Adaptability and resilience in rapidly changing environments
• Solid project management skills and the ability to track and oversee multiple initiatives
• Passion for data and AI enablement, education, and capability uplift
• AI/ML architecture knowledge
• Ability to convert AI concepts into business value
• Integration of AI into enterprise data architecture
• Collaboration with data scientists/engineering for AI-enabled delivery

Closing Date    

• 2026/04/17