Sr. Data Architect

About the job

Job Title: Sr. Data Architect Role Overview We are seeking a Distinguished Data Architect to define, own, and scale an enterprise-grade Data & AI architecture centered on Microsoft Fabric, Fabric IQ, and AI-native platform capabilities, with Databricks positioned as a secondary or hybrid workload engine. This is a strategic technical leadership role responsible for architecting a governed, scalable, AI-ready data foundation that powers Generative AI, Agentic AI systems, RAG architectures, enterprise Copilots, and advanced analytics workloads. You will serve as the highest-level architectural authority across globally distributed engineering teams, driving platform standardization, AI enablement, and long-term enterprise data modernization. Strategic Mandate • Define enterprise reference architecture for Microsoft Fabric • Architect AI-native data platforms enabling Gen-AI and Agentic AI systems • Lead transition from fragmented data platforms to a Fabric-centric ecosystem • Establish global architecture governance and engineering standards • Institutionalize AI-ready semantic layers, data products, and governed AI access Core Responsibilities Enterprise Fabric Architecture Ownership • Define and govern enterprise architecture standards across Microsoft Fabric (OneLake, Lakehouse, Warehouse, Real-Time Analytics, Power BI, Data Factory) • Architect domain-based or centralized workspace strategies with capacity governance • Standardize medallion architecture aligned to data product principles • Define hybrid architecture patterns where Databricks supports advanced Spark/ML workloads Gen-AI & Agentic AI Enablement • Architect AI-ready data foundations to support: • RAG (Retrieval-Augmented Generation) pipelines • Vector indexing and semantic search • Enterprise Copilot integrations • Agentic AI workflows orchestrating actions across enterprise systems • Design governed access patterns for LLM consumption via Fabric IQ • Enable AI workload isolation, monitoring, and scalability • Collaborate with AI engineers to operationalize Gen-AI models securely and reliably Global Engineering Leadership & Governance • Lead architecture review councils across globally distributed teams • Establish engineering standards, reusable blueprints, and AI design guardrails • Define cross-time-zone delivery cadences and architectural quality gates • Mentor senior architects and AI/data engineering leads • Drive documentation maturity and structured governance models Platform Reliability, Scale & FinOps • Architect Fabric capacity planning, performance optimization, and workload segmentation • Establish observability frameworks for data pipelines, semantic models, and AI workloads • Drive cost transparency and compute optimization • Ensure scalable Spark, SQL, and AI execution patterns Governance, Security & Responsible AI • Integrate Microsoft Purview for metadata, lineage, and policy enforcement • Architect role-based access controls and domain-level isolation • Embed Responsible AI principles including model governance and auditability • Ensure regulatory compliance (GDPR, CCPA) across enterprise environments Executive Advisory & Business Alignment • Translate enterprise modernization and AI strategy into architectural roadmaps • Advise CDO/CIO stakeholders on Fabric and Gen-AI adoption strategy • Align platform design to Finance, Supply Chain, Retail, and eCommerce domains • Guide transformation from legacy or Databricks-centric ecosystems to Fabric-first architecture Technical Expertise Required • 10+ years of experience in enterprise data architecture and distributed data platforms • 5+ years designing and implementing Azure-based data ecosystems • Deep hands-on expertise in: • Microsoft Fabric (OneLake, Lakehouse, Warehouse, Data Factory, Real-Time Analytics, Power BI) • Fabric IQ and AI-enabled analytics capabilities • Azure Data Lake Gen2 • Spark (PySpark), SQL, Python • CI/CD using Azure DevOps or GitHub Actions • Experience designing Lakehouse, Data Mesh, or Data Fabric architectures • Proven experience enabling Gen-AI and RAG architectures • Exposure to vector databases and semantic indexing patterns • Experience integrating Databricks for ML experimentation or hybrid architectures • Strong governance integration using Microsoft Purview • Understanding of AI workload orchestration and automation principles (Agentic AI patterns preferred) Leadership Expectations • Experience leading globally distributed engineering teams • Proven success driving enterprise platform transformation initiatives • Ability to influence executive stakeholders • Balance architectural governance with delivery velocity • Strong executive communication and documentation skills Preferred Qualifications • Microsoft Certified: Azure Solutions Architect Expert • Microsoft Certified: Fabric Analytics Engineer Associate (preferred) • Azure Data Engineer Associate • Exposure to: • Azure OpenAI integrations • Agent orchestration frameworks • MLflow / Azure ML • Enterprise Copilot implementations What Makes This Role Distinguished • Enterprise-wide ownership of Fabric & AI architecture • Direct leadership in scaling Gen-AI and Agentic AI platforms • Authority across global engineering teams • Strategic influence over enterprise AI modernization roadmap • Opportunity to architect the next-generation intelligent data foundation