Description

• Translate Finance requirements, business questions and reporting needs into logical, dimensional and physical Snowflake data models.

• Design fact, dimension, aggregate and consumption structures supporting Revenue, Spend and General Ledger use cases.

• Implement Snowflake equivalents for prioritized GL measures using reusable SQL and dynamic calculation patterns.

• Build and apply MTD, QTD, YTD and related period-based calculation utilities, using dynamic tables where appropriate.

• Develop source-to-target mappings, transformation rules, joins, hierarchies, conformed dimensions and data contracts.

• Collaborate with the Finance Semantic & Snowflake Data Architect to implement approved semantic definitions, ontology mappings and metadata requirements.

• Optimise Snowflake models and queries for performance, scalability, maintainability and cost-aware operation.

• Embed data-quality checks, reconciliation controls and traceability from source data to published Finance measures.

• Support unit, integration, regression, performance and user-acceptance testing with clear evidence and defect resolution.

• Provide technical leadership, conduct design and code reviews, and mentor Snowflake data engineers and SQL developers.

• Contribute to CI/CD pipelines, release controls, documentation, runbooks and production-readiness activities.

Skills Required:

8-12 years of overall experience in data warehousing, data modelling, data engineering or business-intelligence platforms.

Strong hands-on experience with Snowflake, advanced SQL and enterprise-scale analytical data models.

Practical experience modelling Finance or regulated-industry data, preferably including GL, P&L, Revenue or Spend reporting.

Experience designing dimensional models, transformation logic, reusable measures and data-quality controls.

Experience leading engineering delivery, reviewing technical work and collaborating directly with business and data stakeholders

Key Skills

Education

Bachelor's degree