Principal Consultant Data Architect

What you'll do

• Own end-to-end target-state architecture for enterprise data and AI platforms using Snowflake and Databricks.
• Define account topology, security models, governance frameworks, and cost/performance architectures for client engagements.
• Design layered data models and semantic layers to support BI, application, and AI consumption.
• Author and maintain the practice's reference architectures, reusable patterns, and engineering standards for dbt and CI/CD.
• Serve as the senior technical authority to advise client executives on platform strategy and AI readiness.
• Provide architecture designs, effort estimates, and technical narratives for pre-sales proposals and statements of work.
• Conduct architecture reviews for engagement teams to ensure designs meet established quality standards before build.
• Mentor junior architects and engineers while driving internal enablement on Snowflake, Databricks, and AI-assisted engineering.

What we're looking for

• Bachelor's degree in Computer Science, Engineering, or an equivalent field.
• Master's degree (preferred).
• 10+ years in data engineering, warehousing, or solution architecture, including 4+ years owning end-to-end architecture on enterprise platforms.
• 5+ years hands-on experience with Snowflake features including Snowpark, Cortex, and Iceberg tables.
• Experience in enterprise data modeling (medallion, dimensional, Data Vault) and dbt Core or Cloud.
• Proficiency in SQL and Python for reviewing, prototyping, and unblocking delivery work.
• Production experience on a major cloud provider (AWS, Azure, or GCP) including networking and security.
• Experience architecting platforms for AI/ML workloads, including RAG patterns and LLM integration.
• SnowPro Advanced: Architect certification (preferred).
• Databricks Certified Data Engineer Professional or Solutions Architect credential (preferred).
• Cloud architecture certification such as AWS Solutions Architect Professional or Azure Solutions Architect Expert (preferred).