Cloud Data Solution Architect – AWS, Azure, GenAI & Microsoft Fabric

Required Skills

• Microsoft Azure
  
• ignio AIOps
  
• AI & GenAI – Products & Tools
  

Primary Skillset

• AWS
  
• Azure
  
• Microsoft Fabric
  
• GenAI Modernization
  

Role Overview

• Lead enterprise-scale cloud, data, and application modernization initiatives.
  
• Design scalable, secure, and business-aligned solutions using AWS, Microsoft Azure, Microsoft Fabric, and Generative AI technologies.
  
• Collaborate with business stakeholders, enterprise architects, engineering teams, and executive leadership to define transformation roadmaps, architect next-generation solutions, and drive successful delivery of cloud-native and AI-enabled platforms.
  

Key Responsibilities

Solution Architecture & Strategy

• Define end-to-end architecture for cloud, data, analytics, and AI transformation programs.
  
• Develop target-state architectures, modernization roadmaps, and migration strategies.
  
• Lead architecture reviews, technology evaluations, and solution governance.
  
• Ensure alignment with enterprise standards, security, compliance, and regulatory requirements.
  

Cloud Modernization

• Architect and implement enterprise solutions on AWS and Microsoft Azure.
  
• Design cloud-native applications using microservices, containers, serverless, and event-driven architectures.
  
• Lead application, infrastructure, and data migration programs from on-premises platforms to cloud environments.
  
• Optimize cloud performance, scalability, resilience, security, and cost.
  

Microsoft Fabric & Data Architecture

• Architect modern data platforms using Microsoft Fabric.
  
• Design Lakehouse, Data Warehouse, Real-Time Analytics, Data Engineering, and Power BI solutions.
  
• Implement enterprise data governance, metadata management, security, and data quality frameworks.
  
• Enable self-service analytics and AI-driven insights across business functions.
  

GenAI & AI-Led Modernization

• Design GenAI-enabled solutions utilizing Azure OpenAI, Amazon Bedrock, Copilot, and LLM-based frameworks.
  
• Drive legacy application modernization using AI-assisted code transformation and reverse engineering approaches.
  
• Implement Retrieval-Augmented Generation (RAG), vector databases, knowledge fabric, and agentic AI architectures.
  
• Identify and deliver AI use cases that improve developer productivity, business efficiency, and customer experience.
  

Stakeholder & Client Management

• Engage with C-level executives, business sponsors, and technology leadership.
  
• Translate business requirements into scalable technical solutions.
  
• Conduct workshops, architecture reviews, solution presentations, and executive briefings.
  
• Provide thought leadership on cloud, data, and AI transformation initiatives.
  

Delivery Leadership

• Guide cross-functional engineering teams through architecture implementation.
  
• Mentor architects, developers, and technical leads.
  
• Support proposal development, RFP responses, estimation, and solution governance.
  
• Ensure successful execution from solution conception through deployment and operationalization.
  

Required Technical Skills

Cloud Platforms

• AWS (EC2, EKS, ECS, Lambda, API Gateway, Redshift, S3, Glue, Aurora, IAM).
  
• Microsoft Azure (AKS, Azure OpenAI, Synapse, Data Factory, Event Hub, Functions, Cosmos DB).
  

Data & Analytics

• Microsoft Fabric.
  
• Power BI.
  
• Databricks.
  
• Azure Synapse Analytics.
  
• Data Lake and Lakehouse Architecture.
  
• ETL/ELT and Data Integration.
  

Architecture & Engineering

• Microservices Architecture.
  
• API and Integration Architecture.
  
• Kubernetes and Containers.
  
• DevOps and CI/CD.
  
• Infrastructure as Code (Terraform, CloudFormation, Bicep).
  
• Security Architecture and Governance.
  

AI & GenAI

• Azure OpenAI.
  
• Amazon Bedrock.
  
• Large Language Models (LLMs) and Prompt Engineering.
  
• Retrieval-Augmented Generation (RAG) Architectures.
  
• AI Agents and Agentic Frameworks.
  
• Vector Databases.
  
• Copilot Ecosystem.
  
• AI Governance and Responsible AI.
  

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline.
  
• Master's degree preferred.
  
• AWS and/or Azure certifications preferred:
  • AWS Solutions Architect Professional.
    
  • Azure Solutions Architect Expert.
    
  • Microsoft Fabric Analytics Engineer.
    

Essential Soft Skills

• Excellent verbal and written communication skills.
  
• Strong customer-facing consulting experience.
  
• Executive-level presentation and stakeholder management capabilities.
  
• Strong analytical and problem-solving skills.
  
• Ability to lead global, cross-functional teams.
  
• Experience working in large enterprise and BFSI environments.
  

Preferred Industry Experience

• Banking and Financial Services.
  
• Insurance.
  
• Capital Markets.
  
• Enterprise Digital Transformation.
  
• Cloud and Data Modernization Programs.
  
• AI/GenAI Adoption Initiatives.