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Position Summary
We are seeking a highly skilled and hands-on Senior Data Architect to lead the design, implementation, and governance of enterprise-scale data platforms built on Microsoft Fabric. This role is responsible for architecting modern data solutions, defining Fabric landing zones, establishing enterprise data standards, and leading the technical delivery of scalable, secure, and AI-ready analytics platforms.
The ideal candidate brings deep expertise in Microsoft Fabric, Azure data services, data architecture, governance, DevOps, and enterprise integration patterns. This is a technical leadership role requiring strategic architecture experience and hands-on implementation capability.
Key Responsibilities
Microsoft Fabric Architecture & Platform Design
Design and implement enterprise-scale Microsoft Fabric solutions across OneLake, Lakehouse, Data Warehouse, Data Factory, Real-Time Intelligence, Power BI, notebooks, and Spark.
Design role-based access control, Microsoft Entra ID integration, workspace governance, sensitivity labels, data-protection controls, and Microsoft Purview integration.
Develop landing-zone blueprints that support scalability, compliance, observability, operational excellence, and repeatable onboarding of business domains.
Define connectivity and network-integration patterns, including gateways, private connectivity considerations, managed identities, secrets management, and hybrid data access.
Data Engineering & Integration Architecture
Architect ingestion and transformation frameworks for ERP, CRM, SaaS, legacy databases, APIs, files, and event streams.
Design Bronze, Silver, and Gold medallion patterns using Fabric Lakehouse and Warehouse capabilities.
Establish standards for data quality, lineage, transformation, metadata, master data management, schema evolution, and source-to-target mapping.
Define batch, near-real-time, and streaming integration patterns while ensuring end-to-end observability and supportability.
Data Governance & Security
Establish governance frameworks using Microsoft Fabric and Microsoft Purview.
Define policies for metadata management, lineage, classification, stewardship, retention, access, auditability, privacy, and compliance.
Design secure architectures using Microsoft Entra ID, MFA, Conditional Access, private endpoints where applicable, Azure Key Vault, managed identities, and Privileged Identity Management.
Ensure solution designs align with enterprise security and regulatory requirements.
Semantic Modeling & Analytics Architecture
Design scalable semantic models for enterprise reporting, self-service analytics, and AI workloads.
Establish conformed dimensions, KPI frameworks, reusable measures, and standardized business definitions.
Guide Power BI architecture, performance optimization, security, deployment, and governance.
Enable governed self-service analytics through certified and reusable semantic models.
AI & Large Language Model Solution Architecture Architect secure, scalable AI and large language model solutions that leverage enterprise data and integrate with platforms such as Azure OpenAI and Microsoft Fabric.
Define data, integration, API, identity, networking, and observability architectures required to operationalize and serve AI capabilities across enterprise applications.
Establish responsible AI standards covering security, privacy, grounding, content safety, evaluation, monitoring, cost management, and human oversight.
Partner with data science, engineering, security, and business teams to evaluate AI use cases and translate them into production-ready architectures.
Dev Ops, Automation & Operations
Implement Fabric DevOps practices using Azure DevOps, GitHub Enterprise, Fabric deployment pipelines, source control, CI/CD automation, and Infrastructure as Code.
Define release management, branching, testing, approval, rollback, and environment-promotion strategies.
Azure OpenAI; generative AI; LLM architecture; retrieval-augmented generation (RAG); embeddings and vector search; semantic search; prompt and agent orchestration; APIs and model serving; responsible AI; content safety; evaluation, monitoring, and cost controls
Success Measures
Successful design and deployment of secure, scalable Microsoft Fabric landing zones.
Consistent adoption of platform, governance, security, and engineering standards across data domains.
Delivery of reliable, performant, reusable data products and semantic models.
Improved data quality, lineage visibility, operational monitoring, and audit readiness.
Reduced reporting latency and platform-administration overhead through automation and standardization.
Establishment of a governed, AI-ready enterprise data foundation.
Candidate Profile
This role is best suited for a senior technical architect who can move comfortably between enterprise strategy, detailed solution design, and hands-on implementation. The successful candidate will communicate effectively with executives, business stakeholders, security teams, platform administrators, and engineering teams while maintaining strong ownership of architecture quality and delivery outcomes.