Principal Consultant, Data Architecture

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.

As a Principal
Consultant, Data Architect in IBM Consulting's Data & AI practice, you own end-to-end solution architecture for enterprise data and AI platforms across a portfolio of client engagements. You are the senior technical authority on the platforms we deliver: you set the target-state architecture, define the standards and reference patterns that engagement teams build to, review their designs, and hold the technical outcome through delivery.

Snowflake is the primary platform;
Databricks and open table formats are secondary.

This role sits one level above the engagement‑aligned Solution Data Architect. Where that role owns one client's platform, this role owns the architecture practice across engagements: it governs engagement architects, resolves cross‑engagement design questions, supports solutioning and pre‑sales, and advises client executives on platform strategy and AI readiness. The role leads through technical authority and mentorship rather than line management, and thrives in a consulting environment where no two engagements are the same.

This role can be performed from anywhere in the US.

• Own end-to-end target-state architecture for enterprise data and AI platforms across concurrent engagements, with Snowflake as the primary platform and Databricks as secondary.
• Define account topology, environment strategy, security and governance model (RBAC, masking, row access, tagging), and cost and performance architecture at Snow Pro Advanced:
  Architect depth.
• Design layered data models (medallion, dimensional, Data Vault) and semantic layers that serve BI, application, and AI consumption.
• Select and justify integration patterns (CDC, event‑driven, file‑based, API, data sharing) against client constraints, and document the trade‑offs.
• Set adoption direction for Cortex AI, Iceberg and open table formats, Snowpark, and data sharing, and define where Databricks or other lakehouse components fit alongside Snowflake.

• Author and maintain the practice's reference architectures, decision records, and reusable patterns for ingestion, transformation, governance, and AI‑ready data.
• Define engineering standards for dbt (or equivalent) model design, materialization, testing, and documentation, and for CI/CD and infrastructure as code across engagements.
• Run architecture reviews for engagement-level architects and lead engineers; approve or redirect designs before build.
• Contribute accelerators, estimation models, and enablement content back to the practice.

• Serve as senior technical authority to client executives: present and defend architecture decisions, roadmaps, and platform investment cases.
• Lead architecture assessments, AI readiness and data maturity evaluations, and translate findings into phased roadmaps.
• Surface architectural risk, scope drift, and technical debt early with proposed resolutions; partner with project and practice leadership on delivery health.

• Provide architecture, effort estimates, staffing…