Data Solutions Architect for AI

Introduction A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

• We are looking for a Data Architect to own the end-to-end technical architecture of our data platform, spanning ingestion, transformation, and consumption layers. This is a hands-on architecture role that sits at the intersection of business and engineering: you will translate business requirements — including incomplete or evolving ones — into clear, actionable technical blueprints, and then guide the engineering teams who bring them to life.

You will act as the technical authority for our modern data stack (Snowflake, dbt Cloud, Azure, Microsoft Fabric, and Python-based orchestration), providing architectural governance and ensuring that every new solution component is a strategic fit within the broader platform and our existing Snowflake and Azure investments.

Preferred Education Master's Degree

Required Technical And Professional Expertise

• 10+ years of experience in data engineering, analytics engineering, or data architecture roles
• Deep expertise in Snowflake — architecture patterns, performance optimization, security, and platform-specific features
• Strong understanding of dbt Cloud and modern ELT/analytics engineering principles
• Hands-on experience with Microsoft Fabric
• Solid grasp of Azure ecosystem, including Azure Blob Storage and related integration patterns

Preferred Technical And Professional Experience

• Hands-on enough to validate technical decisions in the platform — not just theorize about them
• Ability to produce clear, consumable architectural artifacts — diagrams, decision records, standards documentation
• Experience architecting solutions that span multiple vendors and integration touchpoints
• Exposure to Snowflake Cortex, AI/ML data patterns, and the implications of data design on model performance