Data Solution Architect

We are seeking an experienced Data Solution Architect to design and deliver secure, scalable, and citizen-centric data solutions aligned with Enterprise Architecture and digital transformation strategies. The role will lead data architecture, data governance, cloud platforms, analytics, AI/ML, and emerging Agentic AI capabilities across a large, regulated or government environment. Key Responsibilities • Develop enterprise data architecture and strategy aligned with digital transformation and modernization initiatives. • Design scalable data platforms, lakehouses, data lakes, and end-to-end data pipelines supporting batch and real-time processing. • Define and implement Data & AI governance frameworks, operating models, data quality, metadata, lineage, classification, and retention standards. • Architect AI/ML, GenAI, LLMOps, AI Engineering, and Agentic AI solutions for enterprise use cases. • Design and implement modern data architecture patterns including Data Mesh, Data Fabric, Ontology, and Semantic Models. • Define conceptual, logical, and physical data models, including Star, Snowflake, and Data Vault modelling. • Ensure data solutions meet security, privacy, regulatory, and national data protection requirements. • Lead architecture workshops and translate business and government requirements into technical solutions and roadmaps. • Support technology evaluation, procurement, vendor selection, and implementation of data and AI platforms. Required Experience & Skills • Experience in Data Architecture, Data Strategy, and Solution Architecture, preferably within government or highly regulated environments. • Strong hands-on experience with Azure, AWS, GCP, Snowflake, Databricks, Delta Lake, or Apache Iceberg. • Proven experience architecting batch and event-driven/real-time data integration solutions. • Strong knowledge of data governance, data quality, security, compliance, metadata, and lineage. • Experience designing AI/ML and GenAI architectures, including LLMs, Agentic AI, LangChain/LangGraph or similar frameworks, MCP, prompt/context engineering, and AI evaluation. • Strong understanding of Enterprise Architecture principles and alignment with broader digital transformation strategies. • Excellent stakeholder management, communication, workshop facilitation, and technical leadership skills. Show more Show less

Experience in Data Architecture, Data Strategy, and Solution Architecture, preferably within government or highly regulated environments. Strong hands-on experience with Azure, AWS, GCP, Snowflake, Databricks, Delta Lake, or Apache Iceberg. Proven experience architecting batch and event-driven/real-time data integration solutions. Strong knowledge of data governance, data quality, security, compliance, metadata, and lineage. Experience designing AI/ML and GenAI architectures, including LLMs, Agentic AI, LangChain/LangGraph or similar frameworks, MCP, prompt/context engineering, and AI evaluation. Strong understanding of Enterprise Architecture principles and alignment with broader digital transformation strategies. Excellent stakeholder management, communication, workshop facilitation, and technical leadership skills.

Develop enterprise data architecture and strategy aligned with digital transformation and modernization initiatives. Design scalable data platforms, lakehouses, data lakes, and end-to-end data pipelines supporting batch and real-time processing. Define and implement Data & AI governance frameworks, operating models, data quality, metadata, lineage, classification, and retention standards. Architect AI/ML, GenAI, LLMOps, AI Engineering, and Agentic AI solutions for enterprise use cases. Design and implement modern data architecture patterns including Data Mesh, Data Fabric, Ontology, and Semantic Models. Define conceptual, logical, and physical data models, including Star, Snowflake, and Data Vault modelling. Ensure data solutions meet security, privacy, regulatory, and national data protection requirements. Lead architecture workshops and translate business and government requirements into technical solutions and roadmaps. Support technology evaluation, procurement, vendor selection, and implementation of data and AI platforms.