Snowflake Data Modeler/Lead Engineer - Fully Remote

You will work closely with Finance and data stakeholders to translate business requirements into robust Snowflake data and semantic models, supporting Revenue, Spend and General Ledger use cases.

The role is hands-on and combines Snowflake engineering, data modelling, Finance data and semantic modelling, while helping establish an AI-ready data foundation for model-based analytics and agent integration. Snowflake Data Modeler Lead Eng

Key Responsibilities

• Design and implement enterprise-scale Snowflake data models.
• Translate Finance requirements into scalable data and semantic models.
• Develop modelling patterns supporting GL, P&L, Revenue and Spend.
• Build reusable Finance measures and business definitions.
• Develop dimensional, logical and physical data models.
• Design transformation and ETL/ELT logic.
• Implement data-quality, reconciliation, lineage and audit controls.
• Optimise Snowflake workloads and SQL performance.
• Design Snowflake semantic models and governed metrics.
• Establish AI-ready data foundations including metadata, lineage, governance and security.
• Support model-based analytics and AI-agent integration.
• Conduct technical reviews and mentor engineers.
• Work directly with Finance, data and business stakeholders.

• 10-15 years’ experience across data warehousing, data modelling, data engineering or BI.
• Strong hands-on Snowflake experience.
• Advanced SQL.
• Enterprise-scale analytical data modelling.
• Strong dimensional modelling experience.
• Finance data experience, ideally GL, P&L, Revenue or Spend.
• Experience creating reusable measures and transformation logic.
• Snowflake semantic modelling experience.
• Experience with governed metrics and reusable business definitions.
• Experience with data quality, lineage and governance.
• Experience leading technical delivery.

Desirable

• COCO SDK or comparable context/agent integration framework.
• AI-ready data foundations.
• Model-based analytics.
• AI-agent integration with enterprise data.
• Experience within Finance or another regulated environment.