MS Fabric Specialist

Job Description Roles & Responsibilities, Overall 10 Years of Experience Define and govern an enterprise-scale cloud data platform architecture, with Microsoft Fabric as a core platform, spanning data engineering, integration, warehousing, real-time analytics, business intelligence, AI, security, governance, and operations. Translate business strategy into practical architecture, guide delivery teams, and ensure solutions are scalable, reliable, reusable, compliant, and aligned with enterprise standards. ·       Key Responsibilities Design end-to-end cloud data and Microsoft Fabric architectures aligned with business objectives, enterprise data strategy, and cloud standards.  Define platform roadmaps, modernization approaches, reference architectures, reusable design patterns, technology standards, and implementation strategy.  Provide technical leadership and architectural guidance across data engineering, cloud infrastructure, analytics, integration, security, AI, and operations.  Architect metadata-driven ingestion and transformation frameworks using Fabric Data Factory, notebooks, Spark, SQL, and event-driven services.  Design and maintain secure, highly available, scalable batch and streaming pipelines for analytics, operational reporting, and data provisioning.  Design Lakehouse, Data Warehouse, semantic models, distributed processing solutions, and governed data products capable of handling large data volumes.  Integrate enterprise applications, databases, APIs, files, SaaS platforms, on-premises systems, Microsoft Azure services, and other cloud environments.  Define enterprise AI and Generative AI architecture using Microsoft Fabric, Azure AI Services, Azure OpenAI, intelligent analytics, RAG, vector databases, and semantic search capabilities.  Evaluate emerging data and AI technologies, including Agentic AI, Model Context Protocol (MCP), and enterprise automation, and lead proof-of-concept assessments where appropriate.  Own architecture decisions for security, identity, networking, governance, compliance, lineage, data quality, observability, and operational monitoring.  Optimize platform performance, reliability, scalability, cost effectiveness, and operational supportability; act as an escalation point for critical platform and data warehouse issues.  Assess and plan migrations of legacy and on-premises data estates to Microsoft Fabric and Azure, including reconciliation, cutover, and transition considerations.  Collaborate with business and technical stakeholders to gather requirements and translate them into practical, maintainable data solutions.  Provide input to sprint planning, delivery processes, technical standards, automated testing, CI/CD, release management, and infrastructure-as-code practices.  Guide multidisciplinary engineering teams, facilitate architecture workshops, document decisions, promote best practices, and contribute to knowledge sharing and engineering excellence.  Provide strategic technology guidance to senior management and coordinate with cloud providers, subject-matter experts, operations teams, and external service providers.  Required Experience and Skills 10+ years of experience in data engineering, analytics, data architecture, or cloud data platforms, including leadership of enterprise-scale solutions.  Hands-on experience with Microsoft Fabric, including One Lake, Lakehouse, Data Warehouse, Data Factory, Real-Time Intelligence, and Power BI. Strong proficiency in SQL, T-SQL, Python, PySpark, Spark, Delta Lake, data modeling, ETL/ELT, and distributed data processing.  Experience with medallion architecture, domain-oriented data products, metadata-driven ingestion, governed semantic layers, and scalable data provisioning.  Experience architecting cloud and big-data solutions, including Microsoft Azure; familiarity with virtual networks/VPC concepts and multi-tenant resource management is beneficial. Hands-on experience with RAG Qualifications BE Additional Information 8 - 10 Yrs