Senior Data & AI Platform Architect

IBM

Kansas City (KS)

On-site

USD 180,000 - 230,000

Full time

14 days+

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Job summary

IBM Consulting in the United States seeks a Principal Consultant in Data & AI to own end-to-end target-state architecture for enterprise data and AI platforms across engagements, with Snowflake as the primary platform and Databricks as secondary. You will influence architecture strategy, standards, and patterns, and mentor teams to ensure delivery quality.

You will lead architecture reviews, define integration and data modeling approaches, and engage executives on platform investments and AI

Qualifications

Bachelor's degree in Computer Science, Engineering, or an equivalent field.
10+ years in data engineering, warehousing, or solution architecture, including 4+ years owning end-to-end architecture on enterprise data platform engagements.
Client-facing consulting or professional services delivery experience, including executive stakeholder engagement across concurrent engagements.
5+ years hands-on Snowflake: account and warehouse topology, clustering and performance, RBAC and security model, cost governance.
Snowflake platform-native features: Streams, Tasks, Dynamic Tables, Snowpark, data sharing, external volumes and Iceberg tables, Cortex.
Enterprise data modeling across medallion, dimensional, Data Vault, and 3NF approaches.
dbt Core or Cloud: model design, materializations, macros, packages, testing, snapshots.
CI/CD for data platforms (GitLab, GitHub Actions, or equivalent): pipelines, merge request workflows, environment promotion.
Production experience on at least one major cloud (AWS, Azure, or GCP), including storage, IAM, networking and private connectivity, and secrets management.
Experience architecting platforms that support AI and ML workloads, including vector and feature data, RAG patterns, and LLM integration in pipelines.
Experience defining and enforcing architectural standards and reference architectures across multiple delivery teams.
SQL and Python proficiency sufficient to review, prototype, and unblock delivery work.
Demonstrated technical leadership: design and code review, mentoring architects and engineers, and setting technical direction.
Track record contributing architecture and estimates to proposals and statements of work.

Responsibilities

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 SnowPro 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.