Solution Architect — Data & AI Platform

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Solution Architect — Data & AI Platform based in United Arab Emirates. This senior contract opportunity is designed for an experienced architect passionate about the intersection of modern data platforms and artificial intelligence. You will shape AI-ready data capabilities on a modern Databricks Lakehouse foundation, enabling advanced analytics and intelligent applications. The role spans LLM-powered analytics, conversational AI, agentic workflows, governed data products, semantic layers, metadata intelligence, and RAG. You will establish scalable architecture patterns that connect high-quality, governed data with emerging AI capabilities. The position combines strategic architecture leadership with hands-on technical design across data, AI, governance, and platform engineering. You will help define standards that improve data discoverability, reliability, security, and usability for both people and AI systems. This remote contract role is suited to a highly experienced professional comfortable driving complex technology initiatives in a modern cloud environment. Accountabilities • Define and drive the overall Data and AI platform architecture using Databricks, Delta Lake, Unity Catalog, and modern lakehouse design patterns. • Develop scalable architecture patterns that enable AI-ready data products, governed analytics, and enterprise AI use cases. • Architect secure LLM and Generative AI enablement capabilities, including RAG, embeddings, vector search, semantic search, prompt orchestration, model serving, grounding, and AI evaluation. • Design agentic AI capabilities that can support data platform operations, including metadata discovery, catalog enrichment, lineage analysis, and data quality investigations. • Enable AI-assisted documentation generation, pipeline troubleshooting, automated test generation, and operational runbook support. • Establish architecture standards for governed data products, certified metrics, semantic layers, and consistent business definitions. • Define approaches for integrating metadata intelligence and semantic context into AI-driven analytics and data experiences. • Establish secure, scalable, and maintainable patterns for deploying data and AI capabilities across the platform. • Collaborate with engineering, data, AI, and business stakeholders to translate complex requirements into practical architecture solutions. • Promote modern engineering practices, including automation and CI/CD, to support reliable delivery and continuous improvement of data and AI platforms. Requirements • 10+ years of professional experience in solution architecture, data architecture, platform engineering, or closely related technology roles. • Strong experience designing modern data platforms, preferably using Databricks, Delta Lake, and Unity Catalog. • Solid understanding of lakehouse architecture, data governance, metadata management, data products, and semantic modeling. • Practical knowledge of AI/GenAI architecture patterns, including LLMs, RAG, embeddings, vector search, semantic search, model serving, grounding, and AI evaluation. • Experience designing or enabling agentic AI workflows, particularly for data discovery, lineage, quality, documentation, troubleshooting, or platform operations. • Strong SQL skills and familiarity with modern data engineering and analytics ecosystems. • Experience with CI/CD practices and automation for data and AI platform development and deployment. • Ability to design secure and scalable architectures that balance innovation, governance, performance, and maintainability. • Strong understanding of data quality, lineage, metadata, business definitions, and governed metrics. • Excellent analytical, communication, and stakeholder-management skills, with the ability to explain sophisticated technical concepts to both technical and non-technical audiences. • Ability to operate at a strategic level while remaining sufficiently hands-on to evaluate technologies, define architecture patterns, and guide implementation teams. Benefits • Remote work: Work from a location that supports your productivity and professional needs. • Contract engagement: Opportunity to contribute to a high-impact Data and AI platform initiative on a project basis. • Senior-level scope: Take ownership of architecture decisions spanning modern data platforms, AI, governance, and enterprise analytics. • Cutting-edge technology exposure: Work with Databricks, lakehouse architecture, LLMs, RAG, agentic AI, semantic layers, and metadata intelligence. • High-impact projects: Help establish foundational capabilities that enable future AI-powered analytics and intelligent data operations. • Strategic influence: Shape architecture standards and patterns for AI-ready data products and governed enterprise data. • Collaborative environment: Partner with data, engineering, AI, and business stakeholders on complex technology initiatives. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Show more Show less

10+ years of professional experience in solution architecture, data architecture, platform engineering, or closely related technology roles. Strong experience designing modern data platforms, preferably using Databricks, Delta Lake, and Unity Catalog. Solid understanding of lakehouse architecture, data governance, metadata management, data products, and semantic modeling. Practical knowledge of AI/GenAI architecture patterns, including LLMs, RAG, embeddings, vector search, semantic search, model serving, grounding, and AI evaluation. Experience designing or enabling agentic AI workflows, particularly for data discovery, lineage, quality, documentation, troubleshooting, or platform operations. Strong SQL skills and familiarity with modern data engineering and analytics ecosystems. Experience with CI/CD practices and automation for data and AI platform development and deployment. Ability to design secure and scalable architectures that balance innovation, governance, performance, and maintainability. Strong understanding of data quality, lineage, metadata, business definitions, and governed metrics. Excellent analytical, communication, and stakeholder-management skills, with the ability to explain sophisticated technical concepts to both technical and non-technical audiences. Ability to operate at a strategic level while remaining sufficiently hands-on to evaluate technologies, define architecture patterns, and guide implementation teams.

Define and drive the overall Data and AI platform architecture using Databricks, Delta Lake, Unity Catalog, and modern lakehouse design patterns. Develop scalable architecture patterns that enable AI-ready data products, governed analytics, and enterprise AI use cases. Architect secure LLM and Generative AI enablement capabilities, including RAG, embeddings, vector search, semantic search, prompt orchestration, model serving, grounding, and AI evaluation. Design agentic AI capabilities that can support data platform operations, including metadata discovery, catalog enrichment, lineage analysis, and data quality investigations. Enable AI-assisted documentation generation, pipeline troubleshooting, automated test generation, and operational runbook support. Establish architecture standards for governed data products, certified metrics, semantic layers, and consistent business definitions. Define approaches for integrating metadata intelligence and semantic context into AI-driven analytics and data experiences. Establish secure, scalable, and maintainable patterns for deploying data and AI capabilities across the platform. Collaborate with engineering, data, AI, and business stakeholders to translate complex requirements into practical architecture solutions. Promote modern engineering practices, including automation and CI/CD, to support reliable delivery and continuous improvement of data and AI platforms.