Data Solution Architect

Data solution Architect Perm Role: Work Location : Dubai Role Summary: The Data Solution Architect plays a pivotal role in designing and delivering secure, scalable, and citizen-centric data architecture solutions that aligns with the overall Enterprise Architecture needs and vision. This role ensures that data platforms, analytics capabilities, and AI/ML integrations are aligned with core digital strategies, regulatory frameworks, and analytics delivery goals. The architect will work across departments to enable data-driven governance, operational efficiency, and enhanced citizen experiences. Key Responsibilities: Strategic Architecture & Planning • Develop and maintain enterprise data architecture aligned with digital transformation initiatives. • Define data strategies and solutions that support services like citizen services, data transformation and modernization programs • Define AI strategies for Data and AI led Digital transformation initiatives which include Agentic solutions • Define Data and AI governance strategies, operating models, rules and processes • Ensure compliance with national data protection laws and governance models. Solution Design & Delivery • Architect data platforms (data lakes/lakehouses, batch and real-time ingestion, processing and analytics) for various use cases supporting descriptive, predictive and prescriptive analytics • Architect secure end to end data pipelines for ingestion, transformation, and consumption across enterprise entities. • Integrate AI/ML capabilities for enterprise analytics use cases including Agentic capabilities, LLMOps, AI engineering and ML Engineering • Define and document data models (conceptual, logical, physical), dimensional modeling, metadata standards, and lineage tracking for auditability and transparency. • Implement modern Data Architecture patterns like Data Mesh and Data Fabric and have experience in Ontology or Semantic modeling. Governance & Compliance • Establish data governance frameworks including stewardship, quality, classification, and retention policies. • Collaborate with data compliance teams to ensure data architecture supports audit, and compliance requirements. • Design data solutions that implement access control, encryption, and identity federation and data security principles. Stakeholder Engagement • Lead cross-functional workshops with government departments, IT teams, and external partners to gather requirements and present solution designs. • Translate enterprise objectives into technical specifications and data capabilities. • Create and present Data and AI Strategy and Roadmap to key stakeholders. • Support procurement and vendor evaluation for data platforms and analytics tools. Experience and Skills • 15+ years of experience in data solution architecture and data strategy definition in regulated environments. • Proven experience designing and implementing data platforms and data management solutions in government, or other large enterprises. • Hands-on Architecture and implementation experience with cloud data platforms (Azure, AWS, GCP, Snowflake etc.), data integration tools, and analytics frameworks. • Hands-on Architecture and implementation experience with Databricks, Delta lake, Apache Iceberg Lakehouse solutions • Hands on experience in Data Modeling with schema patterns like STAR, Snowflake and Data Vault modeling patterns • Hands on experience in implementing Data Quality using Data Quality tools on Azure Databricks • Architecture definition experience involving designing of batch based and event driven (real time) data integration and management. • Experience with secure data handling, compliance and governance • Experience in defining and implementing AI/ML architecture working with LLMs, Agentic solutions involving Lang family, MCP, Prompt Engineering, Context Engineering, Harness Engineering and AI evals. • Excellent communication and stakeholder management skills, Key Competencies • Strategic Thinking & EA Alignment • Data strategy and Architecture • Cloud Data Architecture definition and implementation • AI/ML Architecture definition and implementation covering GenAI and Agentic solutions. • Technical Leadership in Regulated Environments Show more Show less

15+ years of experience in data solution architecture and data strategy definition in regulated environments. Proven experience designing and implementing data platforms and data management solutions in government, or other large enterprises. Hands-on Architecture and implementation experience with cloud data platforms (Azure, AWS, GCP, Snowflake etc.), data integration tools, and analytics frameworks. Hands-on Architecture and implementation experience with Databricks, Delta lake, Apache Iceberg Lakehouse solutions. Hands on experience in Data Modeling with schema patterns like STAR, Snowflake and Data Vault modeling patterns. Hands on experience in implementing Data Quality using Data Quality tools on Azure Databricks. Architecture definition experience involving designing of batch based and event driven (real time) data integration and management. Experience with secure data handling, compliance and governance. Experience in defining and implementing AI/ML architecture working with LLMs, Agentic solutions involving Lang family, MCP, Prompt Engineering, Context Engineering, Harness Engineering and AI evals.

Strategic Architecture & Planning: Develop and maintain enterprise data architecture aligned with digital transformation initiatives. Define data strategies and solutions that support services like citizen services, data transformation and modernization programs. Define AI strategies for Data and AI led Digital transformation initiatives which include Agentic solutions. Define Data and AI governance strategies, operating models, rules and processes. Ensure compliance with national data protection laws and governance models. Solution Design & Delivery: Architect data platforms (data lakes/lakehouses, batch and real-time ingestion, processing and analytics) for various use cases supporting descriptive, predictive and prescriptive analytics. Architect secure end to end data pipelines for ingestion, transformation, and consumption across enterprise entities. Integrate AI/ML capabilities for enterprise analytics use cases including Agentic capabilities, LLMOps, AI engineering and ML Engineering. Define and document data models (conceptual, logical, physical), dimensional modeling, metadata standards, and lineage tracking for auditability and transparency. Implement modern Data Architecture patterns like Data Mesh and Data Fabric and have experience in Ontology or Semantic modeling. Governance & Compliance: Establish data governance frameworks including stewardship, quality, classification, and retention policies. Collaborate with data compliance teams to ensure data architecture supports audit, and compliance requirements. Design data solutions that implement access control, encryption, and identity federation and data security principles. Stakeholder Engagement: Lead cross-functional workshops with government departments, IT teams, and external partners to gather requirements and present solution designs. Translate enterprise objectives into technical specifications and data capabilities. Create and present Data and AI Strategy and Roadmap to key stakeholders. Support procurement and vendor evaluation for data platforms and analytics tools.