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# Sr. Solution Architect, Data, Analytics & AI

- **Company:** Experis
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Infrastructure, Machine Learning, Snowflake, Microsoft Fabric, Data Management, Azure Synapse Analytics
- **Published:** October 2, 2026
- **Apply:** https://www.experis.com/en/job/413443/sr-solution-architect-data-analytics-ai

## About the Role

Our client is seeking a Sr. Solution Architect, Data, Analytics & AI to join their team. As a Sr. Solution Architect, Data, Analytics & AI, you will be part of the Technology Business Unit supporting the Data & Analytics platform and emerging AI capabilities. The ideal candidate will have a business-first mindset, deep hands-on Snowflake expertise, and the ability to govern and validate production-grade data platform architecture across Microsoft Fabric, Snowflake, and Power BI., + 15+ years of progressive experience in data engineering, data architecture, analytics, or closely related technical disciplines.

 + 5+ years of hands-on, in-depth Snowflake architecture and engineering experience (required).
 + Proven experience architecting and delivering production-grade data platforms on Microsoft Fabric or Azure Synapse Analytics.
 + Strong experience designing data lakehouse architectures and data products at enterprise scale, including medallion patterns (Bronze/Silver/Gold).
 + Experience architecting AI/ML data infrastructure and collaborating with data science/ML engineering teams to translate AI requirements into implementable platform architectures.

## Description

+ Design and own the end-to-end solution architecture for data, analytics, and AI across Microsoft Fabric, Snowflake, and Power BI, ensuring scalable, governed, production-ready outcomes.
 + Serve as the primary deep-subject-matter expert for Snowflake architecture and integration decisions, including data modeling, performance optimization, cost management, and security configuration.
 + Govern the Fabric-to-Snowflake transition by validating an implementation partner's work (dbt models, Snowflake Semantic Views, and Iceberg catalog integration) against Fabric production outputs.
 + Architect and drive decisions on open evaluations that directly impact trust and consistency-semantic/ontology layer, MDM strategy, and data governance/certification approach.
 + Build the foundational data infrastructure for AI/ML workloads, including RAG-aligned architectures and governed data pipelines that enable trustworthy AI answers.
What's Needed?