Data & AI Solution Architect

Data & AI Solution Architect – Data Modelling & Conversational AI Location: Canada Contract Duration: 6 Months, with the possibility of extension based on project requirements About the Role We are seeking an experienced Data & AI Solution Architect to support the design and implementation of enterprise data models, semantic architectures, and conversational AI solutions for the OneData platform . Working as part of the Enterprise Architecture team , you will define scalable and reusable architecture patterns that enable trusted data, self-service analytics, modern data engineering, and conversational AI across the organization. The primary focus of this role will be on enterprise data modelling, semantic engineering, solution architecture, and Databricks Genie conversational AI . You will translate enterprise architecture standards into practical solution designs, reusable reference architectures, and technical guidance that enable HUB & SPOKE delivery teams to independently build trusted, governed, and scalable data products. Key Responsibilities • Design and develop enterprise data models, ERDs, dimensional models, and semantic architectures to support trusted enterprise data products. • Design solution architectures for modern cloud data and AI platforms using Databricks . • Develop semantic architectures using Databricks Metric Views to enable trusted analytics and self-service consumption. • Design and implement architecture patterns for Databricks Genie conversational AI and natural-language data interaction. • Define and promote enterprise standards and best practices across: • Data Products • Data Modelling • Medallion Architecture • DBT • Unity Catalog • Modern Data Engineering • Semantic Modelling • Create reusable architecture patterns, reference designs, frameworks, and implementation guidelines for HUB & SPOKE teams. • Define semantic models and frameworks that support analytics, self-service BI, and conversational AI use cases. • Ensure data and AI solutions are scalable, governed, secure, reusable, and aligned with enterprise architecture standards . • Lead architecture reviews, solution design workshops, technical discussions, and architecture governance sessions. • Conduct technical coaching, office hours, and knowledge-sharing sessions to help delivery teams adopt enterprise standards. • Partner with data engineering, analytics, AI, product, and enterprise architecture teams to translate business requirements into scalable technical solutions. • Provide technical guidance and mentorship to delivery teams throughout the solution lifecycle. • Identify opportunities to improve self-service data consumption, standardization, reusability, and implementation efficiency . Required Qualifications • 8+ years of experience in Enterprise Solution Architecture, Data Architecture, or modern cloud data platforms. • Strong hands-on experience with Databricks and modern data platform architecture. • Strong experience with DBT, Unity Catalog, SQL, and Python . • Deep understanding of: • Enterprise Data Modelling • Dimensional Modelling • Semantic Modelling • Data Product Architecture • Medallion Architecture • Modern Data Engineering • Experience designing enterprise ERDs, logical/physical data models, and reusable data architecture patterns . • Strong understanding of data governance, data quality, security, and enterprise architecture principles. • Strong experience translating enterprise architecture standards into practical solution designs and implementation guidance. • Excellent stakeholder management and communication skills. • Proven ability to lead architecture discussions and guide engineering and delivery teams toward standardized solutions. Preferred / Nice-to-Have Skills • Experience with Databricks Metric Views and semantic layer design. • Hands-on experience with Databricks Genie and conversational AI/data analytics use cases. • Experience designing architecture for