Senior Data Architect – Databricks / Snowflake

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 seeking a Senior Data Architect with deep hands‑on expertise in Databricks and/or Snowflake to support both pre‑sales and delivery within our services organization. This role combines solution architecture, client engagement, delivery leadership, and AI‑focused data strategy. Expected time split: 40% sales support, 60% delivery.

Key Responsibilities
• Support sales by shaping solutions, responding to RFPs/RFIs, and presenting demos and architectures.
• Partner with senior client stakeholders to define data strategy, platform design, and technology direction.
• Lead end‑to‑end data platform implementations on Databricks/Snowflake, ensuring scalable and high‑quality delivery.
• Align data architecture with AI/ML initiatives and guide clients on data readiness for AI.
• Mentor and develop data engineering and architecture teams.
• Contribute to internal best practices, reference architectures, and reusable assets.

• 15+ years in data architecture or data engineering.
• Proven consulting/services experience and ability to influence senior client stakeholders.
• Strong pre‑sales experience including solution creation and RFP responses.
• Hands‑on leadership of large data platform implementations

Must‑Have Technical Skills
• Deep expertise in Databricks and/or Snowflake.
• Strong cloud knowledge (AWS, Azure, or GCP).
• Data modelling, Spark, SQL, ETL/ELT, and orchestration tools.
• Understanding of data governance, security, and modern data platform design.
• Knowledge of AI/ML requirements and how data platforms enable them.

• Experience with lakehouse architectures, MLflow, Delta Lake, Snowpark, Snowpipe, or similar.
• Knowledge of MLOps, data observability, DevOps/CI-CD, and BI tools.
• Cloud or platform certifications.

Key Attributes
• Excellent communication, client‑facing abilities, and solution articulation.
• Hands‑on, consultative, and able to lead teams and delivery.