Data engineer 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.

• Leading data engineering initiatives end-to-end, from requirements gathering to production deployment serving AI use cases.
• Designing and building ELT pipelines loading data from Azure Blob Storage into Snowflake
• Developing and maintaining dbt transformation models to deliver scalable, reliable analytics datasets
• Writing Python scripts for data orchestration and advanced transformations
• Leveraging Snowflake-specific features and Snowflake Cortex for AI-driven use cases
• Acting as a technical bridge between business users and delivery teams.
• Identifying and unblocking delivery bottlenecks before they become problems
• Proposing improvements, new approaches, and solutions.

• Self-driven — you set your own pace and direction
• Comfortable with ambiguity — unclear requirements don't stop you, they challenge you
• Solution-oriented — you focus on removing blockers, not documenting them
• A collaborative communicator — friendly, clear, and effective across technical and non-technical audiences
• Master's Degree
• 5+ year in data engineering or analytics engineering with a modern data stack focus
• 4+ years of hands-on Snoflake experience, including advanced and platform specififc features
• 3+years of hands on dbt Colud experience in production environments
• Solid Python skill for orchestration and transformation use cases
• Strong experience with Azure and Azure Blob Storage integrations
• Будет плюсом: Exposure to Snowflake Cortex and familiarity with ML lifecycle concepts ( training vs inference); Excellent communication skills - able to work smoothly across different vendors and business stakeholders; Relevant professional certifications - Snowflake, Azure; Relevant professional education - AI, Data Science, Big Data, ML or similar; PowerBI skills or experience; Expert level knowledge of dbt

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