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.

Responsibilities

• 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.

Requirements

• 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.

Skills

• Snowflake architecture and engineering
• Microsoft Fabric and Azure Synapse Analytics
• Power BI
• Data modeling, performance optimization, cost management, and security configuration
• dbt models, Snowflake Semantic Views, Iceberg catalog integration
• Semantic/ontology layer design
• Master Data Management (MDM) strategy
• Data governance and certification approaches
• RAG‑aligned architectures for AI/ML workloads
• Governed data pipelines

Benefits

• Own high‑impact architectural decisions that shape how two parallel