Managing Consultant, Data Architect

What you'll do

• Own end-to-end target-state architecture for enterprise data and AI platforms across concurrent client engagements.
• Lead architecture assessments and AI readiness evaluations to create phased roadmaps and investment cases for executives.
• Design layered data models and select integration patterns while documenting all technical trade-offs.
• Author and maintain practice reference architectures, engineering standards, and reusable patterns for data orchestration and governance.
• Conduct architecture reviews for engagement teams to approve designs and resolve cross-engagement technical questions.
• Set adoption direction for platform-native AI capabilities like Snowflake Cortex and Databricks Mosaic AI.
• Manage technical delivery by decomposing architectures into workstreams and reviewing final outputs against approved designs.
• Lead solutioning and pre-sales by providing effort estimates, staffing shapes, and technical narratives for proposals.

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, data warehousing, or solution architecture.
• 4+ years owning end-to-end architecture on enterprise data platform engagements, including at least three lead architect roles.
• 5+ years of hands-on experience at advanced depth on Snowflake or Databricks, with working knowledge of the other.
• Experience in client-facing consulting, including executive stakeholder engagement and advisory across concurrent engagements.
• Proficiency in SQL, Python, CI/CD, and infrastructure as code (Terraform) for data platforms.
• Experience architecting platforms for AI/ML workloads, including RAG patterns and LLM integration.
• SnowPro Advanced: Architect or Databricks Certified Data Engineer Professional/Solutions Architect credentials (preferred).
• AWS Solutions Architect Professional, Azure Solutions Architect Expert, or GCP Professional Data Engineer certification (preferred).