We are seeking an experienced Insurance Data Modeller with strong expertise in Property & Casualty (P&C) Insurance and the London Insurance Market, particularly Lloyd's.

The ideal candidate will have hands-on experience designing conceptual, logical, and physical data models for complex insurance business domains, including Policy, Claims, Billing, Underwriting, Reinsurance, Finance, and Regulatory Reporting.

The role involves developing enterprise-level canonical data models, defining data relationships and mappings, collaborating with business stakeholders, and enabling data integration, governance, analytics, and reporting across insurance systems.

Experience with London Market processes, including Lloyd's, Managing General Agents (MGAs), brokers, and bordereaux reporting, will be highly valued.

Key Responsibilities:

- Design, develop, and maintain conceptual, logical, and physical data models for enterprise insurance applications.

- Develop and maintain canonical data models covering Policy Administration, Claims Management, Billing, Underwriting, Reinsurance, Finance, and Reporting.

- Define entities, attributes, primary and foreign keys, relationships, constraints, and data dependencies.

- Create ER diagrams and document business rules, data definitions, and relationships across insurance systems.

- Ensure data models support scalability, consistency, interoperability, and business requirements.

- Translate complex P&C insurance business requirements into robust data models.

- Model core insurance entities such as policies, policyholders, insured risks, coverages, premiums, claims, reserves, settlements, commissions, and payments.

- Understand London Market insurance and reinsurance processes, including Lloyd's market structures, syndicates, managing agents, brokers, and delegated authority arrangements.

- Support data modelling for MGAs, broker operations, underwriting workflows, and insurance distribution channels.

- Model bordereaux data and support the integration of policy, premium, exposure, and claims information from delegated underwriting arrangements.

- Support reinsurance structures, including treaties, facultative placements, recoveries, and associated financial transactions.

- Design dimensional models, including star and snowflake schemas, for business intelligence, analytics, and regulatory reporting.

- Define fact tables, dimension tables, conformed dimensions, surrogate keys, and measures.

- Support historical data tracking, slowly changing dimensions, and cross-functional reporting requirements.

- Collaborate with data engineering teams to translate conceptual and logical models into physical database structures.

- Ensure data models are optimised for query performance, data quality, and analytical workloads.

- Define source-to-target mappings across insurance applications, operational systems, and enterprise data platforms.

- Map data elements across policy administration, claims, billing, underwriting, finance, and reporting systems.

- Identify data gaps, inconsistencies, redundancies, and transformation requirements.

- Collaborate with application, integration, ETL/ELT, and data engineering teams to ensure accurate data movement and transformation.

- Support data reconciliation and validation during system integration and migration initiatives.

- Work closely with insurance business SMEs, underwriters, claims specialists, finance teams, architects, and data engineers to gather requirements.

- Maintain business glossaries, data dictionaries, metadata, model documentation, and business definitions.

- Support data governance initiatives, including data ownership, lineage, quality standards, and standardisation.

- Ensure alignment between business terminology, canonical data structures, and enterprise data architecture.

- Participate in data model reviews, solution design discussions, and architecture governance forums.

- Use SQL to analyse datasets, validate data relationships, investigate discrepancies, and support data quality checks.

- Work with data warehouse and modern cloud data platforms to implement and validate enterprise data models.

- Collaborate with teams using platforms such as Snowflake and Databricks, where applicable.

- Ensure data models align with enterprise architecture, performance requirements, and data security standards.

Mandatory Skills:

- Strong experience in Property & Casualty (P&C) Insurance.

- Working knowledge of the London Insurance Market, particularly Lloyd's.

- Hands-on expertise in conceptual, logical, and physical data modelling.

- Strong understanding of Entity-Relationship (ER) modelling and relational database design.

- Experience modelling insurance business domains such as Policy, Claims, Billing, and Underwriting.

- Strong SQL skills and understanding of relational databases.

- Experience with data warehousing and dimensional modelling.

- Knowledge of enterprise canonical data models, data mapping, and data relationships.

- Ability to work closely with business stakeholders and translate business requirements into data models.

- Experience with Reinsurance and insurance accounting.

- Knowledge of London Market processes, including bordereaux and delegated authority arrangements.

- Experience working with MGAs, insurance brokers, managing agents, or Lloyd's syndicates.

- Familiarity with premium accounting, commissions, claims settlements, and reinsurance recoveries.

- Experience with Snowflake and/or Databricks.

- Exposure to cloud-based data platforms, ETL/ELT pipelines, and data integration.

- Knowledge of data governance, metadata management, data lineage, and business glossaries.

- Experience with insurance data transformation, migration, and reporting initiatives.