Data Architect

Data Architect – Insurance Finance Transformation

Location: Horsham (3 days onsite)

Contract: Long-term Contract

IR35 Status: Inside IR35

We are seeking an experienced Data Architect with strong expertise in the Insurance domain to support large-scale Finance Transformation initiatives.

The ideal candidate will have deep understanding of insurance data across Policy, Claims, and Finance systems, along with strong capabilities in enterprise data architecture, integration, and data modelling.

Experience working with modern cloud-based data platforms, particularly Databricks / Lakehouse architecture, is highly desirable as the Enterprise Data Platform (EDP) is built on Databricks.

Key Skills & Experience

• Strong Insurance domain experience covering:
• Policy Administration
• Claims
• Finance / Regulatory Reporting
• Proven experience in:
• Enterprise Data Architecture
• Data Modelling
• Data Integration & Data Flows
• Finance Transformation programmes
• Experience designing source-to-target mappings across enterprise systems
• Good understanding of canonical data models and integration patterns
• Exposure to Databricks / Lakehouse architecture preferred
• Strong stakeholder management and communication skills
• Ability to engage effectively with Finance, Business, and Technology teams

Key Responsibilities

• Design end-to-end data architecture for finance transformation initiatives
• Define and govern data flows across insurance and finance platforms
• Create scalable and compliant solution-level data models
• Ensure alignment with enterprise architecture standards and canonical models
• Support financial reconciliation, reporting, and regulatory requirements
• Collaborate with business, finance, and engineering teams to deliver data solutions
• Drive best practices in data governance, quality, and integration

Preferred Experience

• Databricks / Lakehouse implementation exposure
• Experience with Enterprise Data Platforms (EDP)
• Understanding of insurance finance reporting and reconciliation processes
• Exposure to cloud data ecosystems and modern data engineering practices

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