Data Platform Architect – Data & AI Practice

Fresche Solutions

. Help establish and scale the Data & AI Practice .

Posted 10/21/2026full-timeRemote • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing scalable, cloud-native data platforms and enterprise data management, with a strong focus on AWS, Azure, and GCP architectures. Capable of translating business needs into technical solutions while providing leadership in architecture and implementation.

Highest-signal resume keywords

AWS ArchitectureDatabricks ExpertiseSnowflake Lakehouse ArchitectureEnterprise Data ManagementClient-Facing Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Platform DesignData Integration PatternsCloud MigrationData GovernanceData QualityAI EnablementArchitecture PrototypingTechnical DiscoveryArchitecture WorkshopsPOC/MVP Development

Soft Skills

Technical LeadershipStakeholder ManagementSolution ArchitectureCommunication SkillsAdvisory Relationship Building

Tools & Technologies

AzureGCPReltioInformaticaCollibraAlationGenAI ArchitecturesRAGLLM IntegrationAgentic AI

Industry Keywords

Cloud-Native PlatformsData EngineeringEnterprise AILakehouse/WarehouseMDMProduction OperationsArchitecture StrategyTechnology PartnershipsClient ProposalsIntegration Patterns

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformInformatica

About the role

Key responsibilities & impact

Help establish and scale the Data & AI Practice
Work backwards from customer and end-user needs to design solutions delivering measurable business value
Build trusted advisory relationships with customers and guide technology decisions and long-term architecture strategy
Design scalable, cloud-native data platforms covering ingestion, integration, lakehouse/warehouse, processing, governance, analytics, and AI enablement
Design data integration patterns supporting enterprise AI, including RAG, LLM integration, agentic workflows, and MCP-based connectivity
Lead technical discovery, architecture workshops, POCs/MVPs, and guide engineering teams through implementation
Architect migration and integration of legacy enterprise data into modern cloud platforms, incorporating MDM, Data Quality, and Governance
Build reusable reference architectures, accelerators, and implementation patterns
Contribute to technology partnerships and client proposals

Requirements

What you’ll need

Senior hands-on architect capable of designing solutions, explaining architectural choices, building prototypes, and guiding teams through implementation
Strong hands-on experience architecting and implementing enterprise data platforms on AWS
Solid understanding of Azure and GCP architectures, comparative strengths, trade-offs, and evolving technology roadmaps
Deep expertise in Databricks and Snowflake, including lakehouse architecture, data engineering, pipelines, integration patterns, and native AI capabilities
Working knowledge of GenAI architectures, including RAG, LLM integration, agentic AI, and MCP
Strong understanding of enterprise data management, including MDM, Data Quality, Governance, security, and production operations
Familiarity with Reltio, Informatica, Collibra, and Alation, including their integration into enterprise data architectures
Ability to translate business requirements into architecture, develop working prototypes, and provide technical leadership during delivery
Minimum 5 years of direct engagement with North American customers, including technical discovery, architecture discussions, solution advisory, and stakeholder management
Strong client-facing communication, solution architecture, and technical thought-leadership skills

Benefits

Comp & perks

Permanent employment
Remote work arrangement