Azure AI & Databricks Solution Architect

Matrix Global•USA,

About The Position

We are seeking a highly skilled Azure AI & Databricks Solution Architect with expertise in designing, building, and deploying enterprise-scale AI, data, and analytics solutions on Microsoft Azure. This role requires a hands-on technical leader who can architect modern data platforms, develop AI-driven business solutions, and lead cloud transformation initiatives leveraging Azure Databricks, Microsoft Fabric, Azure AI Services, and emerging Generative AI technologies. The ideal candidate will have a strong background in data architecture, machine learning, AI solution development, and cloud migrations, with the ability to translate business challenges into scalable, production-ready AI and data platforms.

Requirements

7+ years of experience in Data Architecture, Data Engineering, AI Engineering, or Solution Architecture.
Deep expertise in Azure Databricks, including Unity Catalog, Delta Lake, Cluster Optimization, and Workspace Administration.
Strong experience with Microsoft Fabric, including OneLake, Data Factory, Data Warehouse, and Power BI.
Hands-on experience building and deploying AI, Machine Learning, and Generative AI solutions.
Experience with Azure OpenAI Service, Azure AI Studio, Cognitive Services, AI Search, and Azure Machine Learning.
Strong proficiency in Python, PySpark, SQL, and Spark SQL.
Experience with Azure Data Lake Storage, Data Factory, Synapse Analytics, Event Hubs, and Key Vault.
Strong understanding of data modeling, Lakehouse architecture, dimensional modeling, and modern analytics platforms.
Experience implementing CI/CD, MLOps, and LLMOps using Azure DevOps or GitHub Actions.
Experience with vector databases, embeddings, semantic search, and RAG architectures.
Proven ability to identify, define, and develop AI use cases that deliver measurable business value.
Experience designing AI solutions from ideation through deployment and operationalization.
Strong understanding of machine learning workflows, model lifecycle management, and AI governance.
Ability to align AI initiatives with business objectives and operational processes.
Experience building production-grade AI applications and intelligent automation solutions.
5+ years of client-facing consulting or solution architecture experience.
Ability to lead technical workshops and executive-level presentations.
Strong stakeholder management and communication skills.
Proven success managing multiple projects and client engagements simultaneously.
Demonstrated ability to mentor technical teams and drive delivery excellence.
Proven experience building AI use cases from concept, architecture, development, deployment, and business adoption.
Experience creating end-to-end AI solutions leveraging Azure AI, Azure OpenAI, Microsoft Fabric, and Databricks.
Ability to translate business problems into scalable AI-powered solutions.
Experience with Generative AI, LLMs, Copilots, Intelligent Search, RAG frameworks, and AI Agents.
Strong understanding of AI architecture, governance, security, and responsible AI practices.

Nice To Haves

Microsoft Azure Certifications (DP-203, AI-102, AZ-305).
Databricks Professional Certification.
Experience with Azure AI Studio and Azure OpenAI.
Experience with LangChain, Semantic Kernel, AutoGen, CrewAI, or similar AI orchestration frameworks.
Knowledge of data governance platforms such as Microsoft Purview and Unity Catalog.
Experience with Infrastructure as Code (Terraform, Bicep).
Experience in Financial Services, Healthcare, Manufacturing, Retail, or Enterprise SaaS environments.

Responsibilities

Partner with business and technical stakeholders to identify, evaluate, and prioritize AI use cases.
Design and develop end-to-end AI solutions from concept through deployment and production support.
Architect Generative AI, Machine Learning, Predictive Analytics, and Intelligent Automation solutions.
Develop enterprise AI frameworks, governance models, and best practices.
Lead AI adoption initiatives and help clients define AI roadmaps and innovation strategies.
Design Retrieval-Augmented Generation (RAG) architectures and AI-powered knowledge management solutions.
Evaluate emerging AI technologies and recommend appropriate architectures and implementation approaches.
Design and implement scalable cloud-native data platforms using Azure Databricks and Microsoft Fabric.
Architect Lakehouse solutions utilizing Delta Lake, Unity Catalog, Fabric OneLake, and Azure Data Lake Storage.
Design highly available and secure AI data foundations capable of supporting advanced analytics and machine learning workloads.
Define enterprise data governance, lineage, privacy, and security frameworks.
Create reference architectures and standards for AI, analytics, and data engineering teams.
Build and deploy machine learning solutions using Azure Machine Learning and Databricks ML.
Develop AI applications utilizing Azure OpenAI, Cognitive Services, Document Intelligence, and AI Search.
Implement MLOps and LLMOps frameworks for model lifecycle management and deployment.
Design model monitoring, evaluation, and continuous improvement processes.
Integrate large language models (LLMs) into business workflows and enterprise applications.
Build intelligent copilots, chatbots, recommendation engines, and AI-powered automation solutions.
Design and optimize large-scale ETL/ELT pipelines using Azure Data Factory, Databricks Workflows, and Fabric Data Pipelines.
Implement real-time streaming and event-driven architectures using Event Hubs and Databricks Structured Streaming.
Develop high-performance data processing solutions using PySpark, Spark SQL, Python, and SQL.
Optimize performance, scalability, reliability, and cost efficiency of cloud data environments.
Support analytics, reporting, and AI initiatives with modern data architecture best practices.
Lead cloud migration initiatives from legacy and on-premise environments to Azure.
Assess existing systems and develop modernization roadmaps.
Migrate data warehouses, Hadoop environments, and analytical platforms to Azure Databricks and Microsoft Fabric.
Establish migration frameworks, testing strategies, and data validation procedures.
Drive platform modernization initiatives that enable AI readiness and advanced analytics capabilities.
Serve as a trusted advisor for data, analytics, and AI transformation initiatives.
Conduct architecture workshops, solution design sessions, and AI discovery engagements.
Present technical recommendations and AI strategies to executive and business stakeholders.
Translate complex technical concepts into business value propositions.
Mentor client teams and internal engineers on AI, Databricks, and Azure best practices.