Finance Semantic & Snowflake Data Architect

The Opportunity

We are looking for a senior Finance Semantic & Snowflake Data Architect to define and govern the Finance semantic architecture connecting Snowflake data assets with Finance business meaning.

This is a senior architecture/design-authority position responsible for the semantic model, ontology, metadata approach, data-consumption patterns and reusable Finance calculation patterns, including approximately 200 General Ledger measures.

Key Responsibilities

• Own the Finance semantic model and architecture.
• Define Finance business ontology and semantic structures.
• Design semantic layers connecting Snowflake data with Finance requirements.
• Define reusable calculation patterns for MTD, QTD and YTD.
• Establish the approach for approximately 200 GL measures.
• Govern Finance metrics and business definitions.
• Define metadata, taxonomy and business glossary approaches.
• Establish lineage and data-governance practices.
• Define data-consumption patterns for reporting and AI.
• Ensure Finance measures are traceable to approved Snowflake data.
• Establish AI-ready data foundations.
• Support model-based analytics.
• Support Snowflake semantic capabilities and agent integration.
• Act as architecture/design authority across delivery teams.
• Work with senior Finance, architecture, governance and engineering stakeholders.
• Document architectural decisions, dependencies and risks.

Essential Experience

• 15+ years' enterprise data architecture/data warehousing/analytics/Finance technology experience.
• Strong Finance data architecture experience.
• Experience with GL, P&L, Revenue, Spend or management reporting.
• Strong Snowflake architecture experience.
• Advanced data modelling.
• Semantic layer architecture.
• Enterprise data architecture.
• Business ontology and taxonomy.
• Metadata and data governance.
• Data lineage and stewardship.
• Reusable Finance measures and calculation patterns.
• Strong senior stakeholder management.
• Experience operating within regulated environments.

Snowflake/Technical

• Snowflake platform architecture.
• Snowflake semantic models.
• Dynamic tables.
• Data modelling.
• Semantic layers.
• Governed analytical consumption.
• Cortex awareness.
• AI-ready data foundations.
• COCO SDK/agent integration awareness.

Certifications: Preferred:

• Snowflake architecture/advanced data engineering certification.
• Data governance certification.
• Enterprise architecture certification.
• Cloud architecture certification.

Best fit

Enterprise Data Architect/Finance Data Architect/Snowflake Architect with significant semantic modelling and Finance transformation experience.