AI Data Architect

Square One Resources is hiring for a strategic data transformation programme focused on developing a modern, AI-ready data platform.

• Proven experience as a Data Architect, Enterprise Data Architect, or similar senior data architecture role.
• Strong background in enterprise data architecture and cloud data platforms.
• Hands-on experience with Azure, Microsoft Fabric, Databricks, AWS, or comparable cloud ecosystems.
• Experience designing data lakes, data warehouses, lakehouses, integration layers, and analytics platforms.
• Strong understanding of data governance, security, identity and access management, and compliance.
• Ability to assess complex and fragmented enterprise environments and translate business requirements into scalable technical solutions.
• Excellent communication and stakeholder management skills with experience working directly with clients and senior leadership.

Optional:

• Experience within manufacturing, logistics, supply chain, finance, or other multi-site enterprise environments.
• Experience integrating ERP, CRM, MES, operational systems, and reporting platforms.
• Knowledge of AI readiness assessments, machine learning platforms, GenAI enablement, or data product development.

• Lead the technical discovery and architecture workstream.
• Assess existing source systems, data flows, integrations, reporting processes, and architectural constraints.
• Identify data fragmentation, architecture gaps, technical risks, and key dependencies.
• Design the target-state ('North Star') data platform architecture.
• Evaluate cloud data platform technologies such as Microsoft Azure, Microsoft Fabric, Databricks, AWS, or similar solutions.
• Recommend the most suitable platform and toolchain based on business needs, scalability, cost, security, operational feasibility, and data residency requirements.
• Define integration patterns, data movement principles, and core platform building blocks.
• Assess AI readiness and define the data architecture required to support AI and GenAI initiatives.
• Provide recommendations on data governance, security, access management, and compliance.
• Assess the technical feasibility of priority business use cases.
• Support implementation planning by contributing to the roadmap, delivery sequencing, and high-level effort estimates.