Azure Data Architect

Azure Architect

Experience · 9–14 years of overall IT experience · 4–6+ years as a Data Architect or Senior Data Engineer / Lead · Proven experience designing enterprise-scale data platforms on Azure Azure Data Expertise · Strong hands-on experience with: o ADLS Gen2 o Azure Synapse Analytics and/or Azure Fabric o Azure SQL, Azure Cosmos DB · Deep understanding of data modeling (conceptual, logical, physical) · Experience with batch and streaming data architectures OpenAI & AI Data Concepts · Working knowledge of Azure OpenAI Service · Strong understanding of: o How LLMs consume and retrieve enterprise data o RAG patterns and vector-based retrieval o Embeddings and semantic search concepts · Experience with or exposure to Azure AI Search / vector indexing Soft Skills · Strong analytical and architectural thinking · Ability to translate business needs into scalable data designs · Excellent communication and documentation skills · Leadership mindset with mentoring capability --- What We Offer · Opportunity to work on AI-driven, data-intensive platforms · Key role in shaping enterprise data and GenAI strategy · Exposure to modern Azure analytics and AI ecosystems · Competitive compensation and growth opportunities Data Architecture & Platform Design · Define and own enterprise data architecture on Microsoft Azure · Design scalable, reliable data platforms including: o Data lakes and lakehouse architectures o Analytical and operational data stores · Establish data standards, reference architectures, and best practices · Lead modernization initiatives from legacy data platforms to cloud-native solutions OpenAI & Generative AI Enablement · Architect AI-ready data foundations for Azure OpenAI and GenAI workloads · Enable data pipelines and architectures to support: o Retrieval-Augmented Generation (RAG) o Embeddings and vector search o AI-powered Q&A, copilots, and analytics · Design data access patterns for secure and governed LLM consumption · Collaborate with application and AI teams to align data models with GenAI use cases Azure Data Services & Analytics · Architect and guide implementations using: o Azure Data Lake Storage (ADLS) o Azure Synapse Analytics o Azure Fabric (OneLake, Lakehouse, Warehouses) o Azure SQL, Azure Cosmos DB · Design batch and real-time data processing using: o Azure Data Factory / Synapse Pipelines o Azure Stream Analytics / Event Hubs (as applicable) · Support BI and analytics integrations (Power BI, semantic models) Data Governance, Security & Quality · Define data governance, lineage, and metadata strategies · Implement data security and access controls using: o Azure AD / Entra ID o RBAC, PIM, and data-level security · Ensure data quality, consistency, and compliance across platforms · Enable responsible and compliant data usage for AI models