_{08th October, 2025}

Head of Domain Architecture - Data & AI


The Head of Domain Architecture - Data & AI is a leadership position responsible for overseeing the architecture of data and AI across the enterprise. This role defines, designs, and maintains strategies and solutions that enable modern, scalable, and secure use of data and AI, while ensuring alignment with overall business goals and objectives.
The position encompasses developing data and AI models and architectures, establishing governance policies, ensuring compliance and security, and optimising data for efficiency, automation, and advanced analytics. The role also involves close collaboration with other domain teams and stakeholders to integrate data and AI with core systems, applications, and processes.
Direct reports may include:

• Data & AI Architects

Accountabilities & Responsibilities

• Overall responsibility for domain architecture strategy, roadmap, and delivery across all programs, projects, and initiatives within Data & AI.
• Partner with the Enterprise Architecture team to lay foundations and roll out enterprise information architecture.
• Define current and target state data & AI architectures, ensuring scalability, integration, and automation.
• Provide leadership in emerging technologies such as Generative AI, advanced analytics, and automation frameworks.
• Oversee solution architecture and design for all initiatives under the Data & AI domain.
• Drive adoption of integration platforms (e.g., Boomi, API-first approaches, automation frameworks) to ensure seamless connectivity across cloud and enterprise systems.
• Enable hybrid and multi-cloud integration, leveraging AWS Data services (e.g., Redshift, Glue, S3, Lake Formation), Google Cloud Platform (GCP), and related ecosystem tools.
• Establish and maintain architecture standards, patterns, and best practices that drive reuse, agility, and cost efficiency.
• Ensure solutions meet key performance indicators including architecture fitness, cost efficiency, speed to delivery, automation, and effective data utilisation.
• Promote a culture of innovation, automation, and continuous improvement within the technology organisation.
• Engage with business and technology stakeholders to ensure alignment of solution architecture with business priorities and desired outcomes.
• Lead, mentor, and grow a team of skilled data and AI architects, fostering a collaborative and delivery-focused culture.

Capabilities & Competencies

• 5+ years of technical experience in data & AI platforms (data warehouses, data lakes, AI/ML models, CDP/DMP, reporting and analytics).
• Strong expertise with cloud-native platforms including AWS and Google Cloud (GCP).
• Proven ability in integration architecture including Boomi and other automation/integration technologies.
• Experience designing automation strategies to streamline data and AI workflows and improve time-to-value.
• Ability to influence and engage senior stakeholders, driving technology-led business strategies.
• Demonstrable experience in establishing data and AI roadmaps and translating them into enterprise-wide capabilities.

Key Metrics

• Architecture Fitness - robust, scalable, and automated solutions that support operational and customer outcomes.
• Data & AI Utilisation - effective use of data and AI products enabling insights, automation, and improved personalisation.
• Integration & Automation Maturity - measurable efficiencies achieved through connected, automated processes and systems.
• Cost Efficiency - reusable, cloud-optimised architectures reduce operational and development costs.
• Stakeholder Alignment - business and technology stakeholder satisfaction through clear alignment with strategic objectives.

Education & Experience

• 10+ years of architecture and design experience, with a strong emphasis on data, AI, cloud, and integration.
• Track record of leading large-scale, multi-domain transformation initiatives.
• Strong background in data and AI architecture, with proven experience implementing modern solutions in AWS and Google Cloud ecosystems.
• Experience introducing automation, integration, and data-driven strategies at scale.

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