Senior Data Analyst - Insurance (AI & Data)

Contract: 6 Months Initially (Outside IR35)Rate: £400-£500 per day Location: Remote-first with occasional travel to London client sites as required

Our client is undertaking a major transformation programme to modernise its data estate and establish a scalable cloud-based platform capable of supporting operational reporting, regulatory requirements, data governance and future AI initiatives.

We are seeking an experienced Lead Data Analyst / Data Modeller with a strong background in the insurance sector to play a key role in defining the enterprise data structures that will underpin the platform.

This position sits between business stakeholders, architects and engineering teams, requiring someone who can combine strong analytical capability with practical data modelling expertise. You will be responsible for translating complex business and operational processes into structured, reusable data models that support multiple products, clients and downstream applications.

The environment includes modern cloud technologies, large-scale relational data sources and complex integration requirements across multiple systems.

• Lead the development of enterprise and subject-area data models across key insurance domains.
• Create conceptual, logical and physical data models that support current operational needs and future scalability.
• Define standardised data structures that can be reused across reporting, analytics and operational processes.
• Establish common definitions, attributes, hierarchies and relationships across multiple data sources.
• Ensure data models align with platform architecture and long-term business objectives.
• Collaborate with architects and engineers to ensure models are practical and implementable.

• Work with SMEs and stakeholders to understand business processes, data challenges and reporting requirements.
• Investigate existing systems and identify opportunities for standardisation and rationalisation.
• Elicit, document and validate detailed data requirements.
• Translate business rules into structured specifications and transformation requirements.
• Identify data gaps, inconsistencies and quality issues across source systems.
• Support requirement workshops and challenge assumptions where necessary.

• Define data quality standards, validation rules and reconciliation requirements.
• Support the creation of controls, monitoring processes and exception management frameworks.
• Help establish governance processes around data definitions, ownership and lineage.
• Drive consistency in metadata, reference data and business terminology.
• Ensure data outputs can support audit and regulatory obligations.

• Partner with engineering teams to support ingestion, transformation and integration activities.
• Produce mapping documentation between source systems and target models.
• Validate that delivered solutions align with agreed business logic and data definitions.
• Support testing activities, data validation exercises and reconciliation processes.
• Contribute to solution design discussions across the broader data platform programme.

• Define structures that support operational, management and regulatory reporting.
• Design data models that enable self-service capabilities and analytical use cases.
• Ensure data structures are capable of supporting future machine learning and AI initiatives.
• Assist in developing reusable datasets that reduce duplication and increase consistency across reporting outputs.

• Proven experience working as a Senior Data Analyst, Lead Data Analyst or Data Modeller.
• Strong background within the Insurance industry.
• Demonstrable experience building enterprise, canonical or logical data models.
• Excellent understanding of relational databases and complex data structures.
• Strong SQL skills with the ability to analyse and profile large datasets.
• Experience working within cloud-based data platforms.
• Knowledge of ETL/ELT processes and modern data integration approaches.
• Experience working alongside data engineers, architects and business stakeholders.
• Strong understanding of data governance, data quality and reconciliation principles.
• Experience delivering within Agile environments.
• Excellent communication and stakeholder management skills.

Experience in some or all of the following is highly desirable:

• AWS
• Databricks
• Delta Lake
• Lakehouse architectures
• Complex SQL environments
• ETL / ELT pipelines
• Change Data Capture (CDC)
• Data lineage and metadata management tools
• Reporting and analytics platforms

• General Insurance, London Market, Specialty Insurance or Broking environments.
• Regulatory reporting and compliance-driven data programmes.
• Data migration or legacy modernisation initiatives.
• Enterprise-wide data governance projects.
• Consultancy or client-facing delivery experience.
• Experience supporting large-scale transformation programmes.

The successful consultant will be comfortable operating in a fast-moving delivery environment and capable of navigating complex stakeholder landscapes.

You'll be:

• Commercially minded and outcome focused.
• Comfortable working with ambiguity.
• Highly analytical with excellent attention to detail.
• Confident influencing both technical and non-technical stakeholders.
• Able to challenge constructively and drive clarity.
• Equally comfortable discussing high-level architecture and field-level data definitions.
• Proactive in identifying risks, assumptions and dependencies.
• Skilled at translating complexity into practical solutions.