Job Summary
Azure Data Architect – Data, AI/ML & Generative AI
About the Role
We are seeking a highly experienced Azure Data Architect to lead the design, implementation, and modernization of enterprise-scale Data & AI platforms on Microsoft Azure. This role will be responsible for defining the data strategy, architecture roadmap, governance framework, and AI/ML capabilities that enable data-driven decision-making across the organization.
The ideal candidate combines strong expertise in Azure Data Services, Databricks, Microsoft Fabric, AI/ML, Generative AI, MLOps, Data Governance, and Enterprise Architecture while partnering with business and technology leaders to deliver scalable, secure, and future-ready solutions.
Key Responsibilities
Key Responsibilities
Data & Cloud Architecture
- Define enterprise data architecture strategy, standards, and best practices.
- Design modern Data Lakehouse, Data Warehouse, and Real-Time Analytics platforms on Azure.
- Architect scalable data solutions supporting analytics, reporting, machine learning, and AI workloads.
- Lead cloud migration and data modernization initiatives from legacy and on-prem platforms.
- Drive architecture governance, design reviews, and technology roadmaps.
Data Engineering & Analytics
- Design and optimize batch and real-time data pipelines using Azure services.
- Establish scalable ETL/ELT frameworks and data integration patterns.
- Build enterprise data models, domain-driven data products, and self-service analytics platforms.
- Improve performance, reliability, scalability, and cost optimization of data platforms.
AI, Machine Learning & Generative AI
- Architect AI/ML platforms leveraging Azure Machine Learning, Azure AI Foundry, and Azure OpenAI.
- Design and implement end-to-end MLOps frameworks for model development, deployment, monitoring, and lifecycle management.
- Develop Generative AI use cases including:
- AI Assistants & Copilots
- RAG (Retrieval Augmented Generation)
- Enterprise Knowledge Search
- Conversational AI
- Intelligent Document Processing
- AI Agents
- Collaborate with Data Scientists and AI Engineers to operationalize AI solutions at scale.
Data Governance & Security
- Establish enterprise data governance, metadata management, lineage, and data quality frameworks using Microsoft Purview.
- Define security architecture, access controls, encryption, compliance, and regulatory standards.
- Ensure adherence to enterprise security, privacy, and Responsible AI principles.
Leadership & Stakeholder Management
- Act as a trusted advisor to business and technology leadership.
- Lead solution architecture workshops and executive presentations.
- Mentor architects, data engineers, and technical teams.
Support strategic initiatives, innovation programs, and pre-sales engagements
Skill Requirements
Required Technical Skills
Azure Data Platform
- Azure Data Factory (ADF)
- Azure Databricks
- Azure Synapse Analytics
- Azure Data Lake Storage Gen2
- Azure SQL Database
- Event Hub
- Stream Analytics
- Microsoft Fabric / OneLake
- Power BI
AI & Machine Learning
- Azure Machine Learning
- Azure AI Foundry
- Azure OpenAI Service
- GPT/LLM Technologies
- RAG Architecture
- AI Agents and Copilot Solutions
- Vector Databases & Semantic Search
- MLOps & MLflow
Programming & Data Engineering
- Python
- PySpark
- SQL
- Spark Framework
DevOps & Cloud Engineering
- Azure DevOps
- GitHub Actions
- Terraform/Bicep
- Docker
- Kubernetes (AKS)
- CI/CD Automation
Governance & Security
- Microsoft Purview
- RBAC
- Managed Identity
- Key Vault
- Data Encryption
- Enterprise Security & Compliance Frameworks
Other Requirements
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
- 10+ years of experience in Data Engineering, Analytics, or Data Architecture.
- 5+ years of hands-on experience designing and delivering Azure-based data solutions.
- Proven experience building enterprise-scale Data Lakes, Lakehouses, and Analytics platforms.
- Strong expertise in AI/ML, MLOps, and Generative AI implementations.
- Experience leading architecture teams and engaging with executive stakeholders.
Preferred Certifications
- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Certified: Azure Data Engineer Associate
- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Fabric Analytics Engineer Associate
- Databricks Certification
- TOGAF or Enterprise Architecture Certification
What Success Looks Like
- Delivery of scalable, secure, and cost-efficient Azure Data & AI platforms.
- Successful implementation of AI/ML and Generative AI capabilities.
- Improved data governance, quality, and compliance.
- Accelerated insights and business decision-making through modern analytics.
- Establishment of enterprise-wide Data & AI architecture standards.
Keywords
Azure Data Architect, Microsoft Fabric, Databricks, Synapse Analytics, Azure OpenAI, Azure AI Foundry, Azure ML, GenAI, GPT, RAG, AI Agents, MLOps, Data Lakehouse, OneLake, Purview, Power BI, Enterprise Data Architecture, Cloud Transformation, Data Governance, AI Platform Architect.