Data Modeler (Banking)

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Senior Data Modeller - Banking (Contract)

Location: Glasgow (Hybrid - 2 days onsite per week) Start Date: Immediate Duration: Initial 6 months (extension likely) Sector: Investment Banking

Engagement Context

Our client, a leading consultancy delivering strategic data transformation across the banking sector, is seeking a Senior Data Modeller to support a high-impact programme focused on post-bind insurance data. The successful candidate will play a critical role in designing scalable, compliant data models that underpin operational reporting, financial reconciliation, and regulatory alignment across multiple specialty lines.

Key Responsibilities

Lead the design and delivery of conceptual, logical, and physical data models across post-bind domains Collaborate with data architects, business analysts, and actuarial teams to translate complex business requirements into structured data assets Apply Data Vault 2.0 methodology to support auditability, scalability, and lineage tracking Model data for ingestion into Snowflake, ensuring compatibility with cloud-native architecture and downstream analytics Ensure models support reconciliation of premium and claims, aged debt tracking, reserve movements, and regulatory reporting Document metadata, data dictionaries, and lineage to support governance and compliance Engage with stakeholders across finance, operations, and claims to validate model assumptions and ensure business alignment Required Experience & Skills

Extensive experience as a Data Modeller within the FS Market, with demonstrable expertise in data Proficiency in Data Vault 2.0 and dimensional modelling techniques Hands-on experience with Snowflake and cloud-based data platforms Ability to model across multiple specialty lines (e.g., marine, aviation, cyber) Strong stakeholder engagement and documentation skills

Clear documentation and stakeholder alignment across finance, operations, and actuarial domains Seamless integration of models into Snowflake and downstream analytics pipelines Contribution to a broader data transformation programme with measurable impact on operational efficiency and regulatory compliance