Azure Sr. Data Architect

GENERAL DESCRIPTION & RESPONSIBILITIES 

The Senior Data Architect is a leader and hands-on builder, combining the technical depth of an Azure Data Engineer with the solutioning expertise of a Solution Architect. This role will partner with clients to envision, design, and deliver enterprise-grade solutions leveraging the Microsoft technology stack. 

You will lead requirements-gathering sessions, architect scalable technical solutions, and contribute as a developer to build and deliver working systems. You will also bring a high-level understanding of the Data & AI landscape, including Microsoft Fabric, Microsoft Purview, and Azure Databricks, enabling clients to modernize their operations through intelligent solutions. 

This position will collaborate across Cyclotron’s sales, delivery, and project management organizations in service of our clients. 

Key Attributes of the Role: 

• Balance visionary solution architecture with hands-on technical execution. 

• Bridge client business needs with technical feasibility using the Microsoft cloud stack. 

• Provide thought leadership on AI, cloud, and modern application development. 

• Mentor project teams while remaining capable of individual technical contribution. 

PLACEMENT CRITERIA & REQUIREMENTS 

• 10+ years of application development and architecture experience, including 4-5+ years in data or analytics architecture on Azure in consulting or enterprise environments. 

• Deep expertise in Microsoft Azure Data & AI services, including Azure Synapse/Fabric Data Warehouse, Azure Data Lake Storage, Azure Databricks and/or Microsoft Fabric, Azure Data Factory/Fabric Data Factory, and Azure SQL. 

• Strong hands-on background with Python, SQL, and PySpark for data engineering; familiarity with .NET/C# and RESTful APIs for integration with application and API layers 

• Experience leading requirements definition, data strategy, and technical design workshops, and translating business goals into data platform and analytics architectures and roadmaps. 

• Familiarity with AI and Microsoft’s AI ecosystem (Azure OpenAI, Cognitive Services, Azure ML). 

• Strong understanding of data engineering concepts, including Databricks, Synapse, and data governance (Purview, Unity Catalog). 

• Prior experience leading cross-functional teams and driving end-to-end solution delivery. 

• Current Microsoft certifications preferred, such as: Microsoft Certified: Azure Data Engineer Associate, Azure Enterprise Data Analyst Associate, Azure Solutions Architect Expert, Microsoft Fabric Analytics Engineer Associate, Azure AI Engineer Associate. 

• Databricks and/or Fabric certifications (e.g., Databricks Data Engineer Professional, Lakehouse fundamentals, or Microsoft Fabric certifications) strongly preferred. 

TECHNICAL SKILLS REQUIRED  

General Architecture & Cloud Services 

• Azure Data Lake Storage (ADLS) for scalable data lake architectures. 

• Azure Synapse Analytics and/or Microsoft Fabric (Data Warehouse, Lakehouse, Notebooks, Pipelines) for analytics workloads. 

• Azure API Management (APIM). 

• Azure DevOps and/or GitHub Actions (CI/CD). 

• Azure Data Factory or Fabric Data Factory for ETL/ELT pipelines and orchestration. 

• Azure Key Vault and role-based access control (RBAC)/managed identities for secrets, credentials, and platform security. 

Data & Analytics 

• Familiarity with Azure OpenAI Service and Azure AI Search/Cognitive Search for intelligent applications, RAG patterns, and embedding/vector search. 

• Experience designing or integrating AI/ML pipelines using Azure Machine Learning or Databricks ML (model training, deployment, and monitoring) is desirable. 

• Azure Data Factory (ADF) for ETL/ELT pipelines. 

• Understanding of Microsoft Copilot extensibility (e.g., plugins, Graph connectors, Copilot Studio) and how data architecture enables secure, governed Copilot scenarios is a plus. 

• Microsoft Purview (data governance). 

• Power BI for dashboards and reporting. 

DESIRED SKILLS 

Application & Integration 

• Experience collaborating closely with application and integration teams using Azure API Management, Azure Functions, Logic Apps, and microservices patterns to expose data services. 

• Knowledge of event-driven and message-based integration using Event Hubs, Serv