Finance Semantic & Snowflake Data Architect

The Finance Semantic & Snowflake Data Architect will define and govern the Finance semantic model that connects Snowflake data assets with Finance business meaning. The role owns the semantic model, ontology, metadata approach, data-consumption patterns, and reusable calculation patterns for MTD, QTD and YTD, including the approach for approximately 200 General Ledger measures. The role will also establish an AI-ready data foundation, enable model-based analytics, and support agent integration using Snowflake semantic capabilities and the COCO SDK.

• 15+ years of overall experience in enterprise data architecture, data warehousing, analytics or Finance technology.
• Demonstrated experience architecting Finance data platforms and semantic layers for GL, P&L, Revenue, Spend or management-reporting domains.
• Strong experience with Snowflake architecture, advanced data modelling, semantic models and governed analytical consumption.
• Experience defining business ontologies, metadata models, lineage and data-governance operating practices.
• Proven ability to work with senior Finance, data, architecture, governance and engineering stakeholders in a regulated environment.
• Bachelor's or master's degree in computer science, Information Systems, Engineering, Finance Technology or a related discipline.
• Snowflake architecture or advanced data engineering certification is preferred.
• Data governance, enterprise architecture or cloud architecture certification is advantageous.
• Finance concepts and measures are consistently defined, governed and traceable to approved Snowflake data.
• Semantic assets support reporting and AI consumption without bypassing agreed business rules and entitlements.
• Dynamic calculation patterns and the GL-measure approach are reusable, testable and understood by delivery teams.
• Architecture decisions, dependencies and risks are documented and resolved through the agreed governance forums.

Capability Area Expected Proficiency Finance domain General Ledger, P&L, Revenue, Spend, management reporting and financial measures

Architecture Enterprise data architecture, semantic layers, logical modelling and consumption patterns

Snowflake Snowflake platform architecture, semantic models, dynamic tables and Cortex awareness

Governance Ontology, taxonomy, business glossary, metadata, lineage and stewardship

Calculation design MTD, QTD, YTD, reusable measure patterns and metric governance

Leadership Executive communication, design authority, facilitation and cross-team decision-making