Solution and Data Architect
Key Responsibilities:
Architectural Oversight:
Own and evolve the overall solution architecture, including application, data, integration, and security layers, ensuring alignment with Wolseley’s IT policies and cloud infrastructure (Oracle/Azure)
Data Architecture Leadership:
Design and maintain the future-state data architecture, supporting automated quote intake, product resolution, pricing, stock availability, and order fulfilment.
Integration and Data Flow:
Architect seamless integration between Wolseley APIs (product, pricing, stock, order submission) and the application’s operational store, catalogue index, and audit logs.
Governance and Compliance:
Define and enforce data governance frameworks, retention schedules, and compliance (GDPR, auditability), minimising PII and ensuring secure handling of sensitive data
AI/ML Enablement:
Enable ingestion and transformation of historical quote/order data for AI advisory features, product recommendations, and pricing guardrails. Collaborate with AI/ML engineers to support NLP-based product resolution and audit-driven enhancements.
Operational Readiness:
Provide documentation, training, and handover artefacts for operational support, monitoring, and troubleshooting. Ensure all features delivered are tested and meet acceptance criteria.
Stakeholder Engagement:
Work closely with business, sales, and IT stakeholders to clarify requirements, facilitate decision-making, and support pilot deployment and evaluation.
Essential Skills & Experience:
Proven Experience:
Demonstrable track record as a Solution and Data Architect in large-scale, cloud-based solutions (preferably B2B quoting domains).
Cloud Platforms:
Expertise in Oracle Cloud and/or Microsoft Azure, including data warehousing, integration, and analytics.
API Integration:
Deep understanding of secure API design, authentication (OAuth2, SSO), and data flow between distributed systems.
Data Modelling:
Strong skills in relational and NoSQL modelling, catalogue indexing, and operational data stores (PostgreSQL, Elastic/OpenSearch, etc.).
AI/ML Familiarity:
Experience supporting AI/ML initiatives, including NLP, product matching, and audit-driven enhancements.
Compliance & Security:
Knowledge of GDPR, data retention, encryption, and audit requirements for enterprise data solutions.
Tools:
Familiarity with Power Platform, observability stacks (OpenTelemetry, Application Insights, Grafana), and CI/CD pipelines (Azure DevOps, GitHub Actions, Terraform).
Desirable attributes:
Excellent communication and stakeholder engagement skills;
Analytical problem-solving and attention to detail;
Ability to work collaboratively in agile, cross-functional teams;
Experience with data governance in regulated environments.
Deliverables:
Oversight and evolution of the solution and data architecture;
Integration and mapping specifications for Wolseley APIs;
Data governance and compliance artefacts;
Operational support documentation and training materials;
Contributions to AI/ML enablement and audit frameworks;
Review and refinement of the existing Low Level Solution Design (LLD).
