Data Solutions Architect for AI

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. 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. 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 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 Poland Software Engineering Hybrid Professional Multiple Cities WARSZAWA Krakow WROCLAW (0109) IBM Polska Sp. zo.o. Analytics Architecture Artificial Intelligence Data Architecture Design Documentation Engineering Integration Machine Learning Optimization Records Security Azure Data Engineering Snowflake Data Warehouse Microsoft Azure Blob Storage