Data Platform Architect – Data & AI Practice - Remote - FS463

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What you’ll work on

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Design scalable cloud-native data platforms covering ingestion through AI enablement
Design data integration patterns for RAG, LLM, agentic AI and MCP connectivity
Lead technical discovery, architecture workshops, and POCs/MVPs
Architect migration of legacy enterprise data into modern cloud platforms
Build reusable reference architectures, accelerators, and implementation patterns

From the employer’s posting

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

Tools in this posting

AWS
Azure
Databricks
GCP
Snowflake

Source

Required Expertise & Experience - Strong hands-on experience architecting and implementing enterprise data platforms on AWS, with a 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. Strong architectural familiarity with both platforms is expected.

- Strong hands-on experience architecting and implementing enterprise data platforms on AWS, with a 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. Strong architectural familiarity with both platforms is expected. - Working knowledge of GenAI architectures, including RAG, LLM integration, agentic AI, and MCP.

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Status in our records: No longer listed
First seen by us: Oct 19, 2026 · 2 days ago
Recorded sightings: 2
Last seen by us: Oct 20, 2026
Reposted: once since Oct 19, 2026

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Job description

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Profile: Senior hands-on architect who can design solutions, explain architectural choices, build prototypes, and guide teams through implementation.

Role Overview
We are looking for a hands-on Data Platform Architect to help establish and scale our Data & AI Practice. The role combines modern cloud data architecture, technical solutioning, client advisory, and engineering leadership to deliver enterprise data modernization and AI-ready platforms.
Key Responsibilities

Customer Obsession: Work backwards from customer and end-user needs to design solutions that deliver measurable business value. Build trusted advisory relationships with customers, guiding technology decisions and long-term architecture strategy.
Platform Architecture: Design scalable, cloud-native data platforms covering ingestion, integration, lakehouse/warehouse, processing, governance, analytics, and AI enablement.
AI-Ready Architecture: Design data integration patterns supporting enterprise AI, including RAG, LLM integration, agentic workflows, and MCP-based connectivity.
Hands-on Solutioning: Lead technical discovery, architecture workshops, POCs/MVPs, and guide engineering teams through implementation.
Modernization: Architect migration and integration of legacy enterprise data into modern cloud platforms, incorporating MDM, Data Quality, and Governance.
Practice Development: Build reusable reference architectures, accelerators, and implementation patterns, and contribute to technology partnerships and client proposals.

Required Expertise & Experience

Strong hands-on experience architecting and implementing enterprise data platforms on AWS, with a 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. Strong architectural familiarity with both platforms is expected.
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 leading platforms such as 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.
North American Customer Experience: 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.

Preferred: Experience in enterprise modernization programs, AI-ready data platforms, and consulting or practice-building environments.

Apply Today: freschesolutions.com/careers/

#LI-Remote

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Pay: No pay amount identified in the saved description.
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Follow Us: LinkedIn #LI-Remote
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