Senior Data Architect

The Data Architect is responsible for shaping and driving the Momentum Investments’ data strategy

through the design, oversight, and enhancement of the enterprise data architecture. This role

ensures that all data initiatives, platforms, and models align with the Group’s overarching data

framework and strategic direction. A key focus of the role is translating business strategy into

practical, scalable data capabilities. The Data Architect influences and educates stakeholders on

data platforms, best-practice usage, and the value of data-driven decision-making.

The role operates as a strategic advisor to business and technology leadership, influencing

enterprise data and AI investment decisions, platform modernisation, and the adoption of datacentric

operating models. The position oversees the implementation and monitoring of data-related

work and projects to ensure alignment with architectural standards, governance practices, and longterm

data capability maturity.

Key Performance Areas

• 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
• Own and drive the enterprise-wide data architecture roadmap across multiple business domains and platforms
• Provide strategic input on the evolution of data and AI capabilities, platforms, and processes to support business strategy
• Translate strategic objectives into tactical implementation plans for data and AI projects and platform enhancements
• Design, refine, and govern enterprise data and AI models, flows, and integration patterns to ensure consistency, scalability, and interoperability
• Define target-state architecture and ensure alignment of all initiatives to enterprise architecture principles
• Monitor and evaluate the execution of data and AI initiatives to ensure adherence to standards, architectural principles, and expected business value
• Establish and maintain data and AI architecture standards, reference architectures, design patterns, and supporting documentation
• Identify opportunities to optimise data availability, data quality, and data utilisation across the organisation
• Provide architectural oversight across multiple concurrent strategic programmes and initiatives

Perspective: Finance

Ensure strategic data and AI decisions balance long-term sustainability with cost-effectiveness

Influence and guide data platform and AI investment decisions (including cloud, tooling, and advanced analytics capabilities)

Evaluate data platform and AI investments to ensure alignment with architectural direction and optimal return on investment

Support financial and business analytics functions through accurate, well-governed data structures and processes

Track and optimise costs associated with storage, compute, and data movement across environments

Identify opportunities for data value realisation and monetisation through advanced analytics and AI

Perspective: Client Services / Stakeholder Engagement

Influence, guide, and educate business stakeholders on data platform capabilities, AI opportunities, appropriate usage, and data-driven decision-making

Serve as a key advisor on data and AI implications of business initiatives, ensuring alignment with architectural principles and governance

Act as a trusted advisor to senior and executive leadership on data and AI strategy and related investment decisions

Promote and embed a culture of responsible data usage and ownership across the organisation

Translate complex data and AI architecture concepts into clear, accessible business language

Provide consultation and training to uplift data and AI literacy and capability across teams

Perspective: People

Foster a collaborative, cross-functional environment with shared accountability for data assets

Mentor and support team members involved in data and AI engineering, analytics, and data management

Promote continuous learning and development related to modern data and AI practices, tools, and frameworks

Encourage knowledge sharing to uplift organisational data and AI capability maturity

Provide technical leadership and thought leadership across data communities within the organisation

Qualifications & experience

Bachelor’s degree in Computer Science, Information Technology, or a related field

Advantageous: Certifications in data architecture, data management, cloud platforms, data analytics, machine learning, applied AI, or enterprise architecture

8–12+ years’ experience in data architecture, data modelling, data analytics, machine learning, applied AI, or enterprise data management

Proven experience in leading or shaping enterprise-scale data architecture and transformation initiatives

Deep understanding and proven success in building data frameworks, embedding data governance, managing metadata, and creating and socialising master data principles

Strong proficiency in database technologies, data integration patterns, and modern data platforms (cloud and on-premise)

Proven experience with Azure, AWS, or Google Cloud data services

Experience across multi-domain or complex data environments, ideally within financial services or similarly regulated industries

Proven experience in influencing stakeholders and driving the adoption of data practices

Demonstrated experience in strategic and technical AI/analytics leadership, AI-driven opportunity identification, and shaping AI and analytics capability roadmaps

Competency

Demonstrates strong analytical, conceptual, and data-modelling capabilities

Applies strategic thinking to translate business goals into clear architectural direction

Exhibits excellent communication, stakeholder engagement, and influencing skills

Shows adaptability and resilience within dynamic, rapidly evolving environments

Possesses solid project management expertise with the ability to coordinate and oversee multiple initiatives simultaneously

Displays a strong passion for data and AI enablement, education, and capability uplift across the organisation

Holds sound knowledge of AI and machine learning architecture

Able to effectively translate AI concepts into tangible business value

Experienced in integrating AI solutions into enterprise data architectures

Collaborates effectively with data scientists and data engineers to enable AI-driven delivery

Strong commercial awareness and ability to balance innovation with cost and value outcomes