Solutions Architect

Architecture Vision:

• Set the vision for enterprise customers' data architecture, from discovery to target-state schemas.
• Design identity matching rules and close data gaps for activation-ready data.

Agent Direction:

• Direct AI agents to profile warehouses, generate models, and review every line they produce.
• Own the resulting models and performance, regardless of who or what typed them.

Customer Success:

• Define success metrics with the customer before the build and defend results to senior leaders.
• Remain the named architect after handoff, supporting model changes and new data sources.

Product Feedback:

• Bring gaps and insights back to product teams to improve the platform.
• Build reusable reference architectures for future engagements.