Data Architect-Snowflake/DBT/Azure

Arthur J. Gallagher · London

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At Gallagher, we help clients face risk with confidence because we believe that when businesses are protected, they’re free to grow, lead, and innovate. You’ll be backed by our digital ecosystem: a client-centric suite of consulting tools making it easier for you to meet your clients where they want to be met. Advanced data and analytics providing a comprehensive overview of the risk landscape is at your fingertips.

Here, you’re not just improving clients' risk profiles, you’re building trust. You’ll find a culture grounded in teamwork, guided by integrity, and fueled by a shared commitment to do the right thing. We value curiosity, celebrate new ideas, and empower you to take ownership of your career while making a meaningful impact for the businesses we serve.

If you’re ready to bring your unique perspective to a place where your work truly matters; think of Gallagher.

As our Data Architect, you will play a key role in designing and delivering a modern cloud-based data platform that underpins the organisation's data and analytics capabilities. Working within a complex insurance environment, you will define the future-state data architecture, champion best practices in data modelling and governance, and help create a scalable, data-driven foundation for the business.

Leveraging your expertise in Snowflake and dbt, you will enable the delivery of trusted, well-governed data that supports critical functions including analytics, pricing, risk, and strategic decision-making across the organisation.

This role is based in London and you are expected to be in two days a week.

Architecture & Strategy

• Define and implement the enterprise data architecture aligned to insurance business priorities (underwriting, claims, actuarial, finance)
• Design and optimise Snowflake-based data platforms, ensuring scalability, security, and cost efficiency
• Lead the transition from legacy policy, claims, and finance systems to modern cloud data solutions
• Establish architectural patterns supporting data domains, data products, and reusable assets

Data Modelling Skills & Experience

• Excellent understanding of conceptual, logical, and physical data modelling principles.
• Experience designing enterprise data models, reporting marts and business specific data products.
• Ability to model complex business relationships, hierarchies, and many-to-many relationships.
• Proficiency in dimensional modelling techniques including star schemas, snowflake schemas, facts, dimensions, and slowly changing dimensions (SCDs).
• Experience producing ERDs, logical data models, business data models, and data dictionaries.
• Strong knowledge of data normalization and denormalization techniques.
• Experience defining and documenting business rules, data lineage, data ownership, and metadata.
• Experience working with Master Data Management (MDM) solutions, including integrating mastered data into enterprise data models and analytical platforms.
• Understanding of data quality, reconciliation, and data governance considerations within data model design

• Previous experience as a Data Architect working in the the Insurance Industry is essential for this position.  An understanding of insurance and brokerage data domains and their interdependencies is required.
• Experience modelling data across key business subject areas including:
  • Client and customer
  • Policy lifecycle
  • Risk and coverage
  • Claims management
  • Finance, premium, commission, and brokerage transactions
  • Insurer
  • Regulatory, compliance, and conduct reporting
  • Ability to develop enterprise data models that support operational processes, management information (MI), regulatory reporting, and analytics.

• Understanding of how data flows across policy administration, claims, finance, CRM, and external market systems.
• Ability to translate complex insurance business concepts into scalable and reusable data models.
• Design and govern dbt-based transformation frameworks, including modular, testable, and well-documented models
• Establish best practices for ELT pipelines, lineage, and dependency management
• Enable self-service analytics through curated semantic and presentation layers
• Drive automation, CI/CD, and testing across the data lifecycle

• Commercial awareness of insurance value chains and drivers

• Strategic but pragmatic—able to balance architecture vision with delivery reality

• High attention to data accuracy, auditability, and compliance

• Excellent stakeholder management at senior and executive level

• Comfortable operating across hands-on delivery and architectural oversight

At Gallagher, we believe supporting our colleagues goes far beyond the role itself. For more information, visit our Benefits page.

• Competitive compensation
• Comprehensive benefits programs designed to support your well-being 
• Career development opportunities and ongoing learning 
• A collaborative, people-first culture with accessible leadership 
• The opportunity to do meaningful work with global reach and local impact 

At Gallagher, we are dedicated to building an inclusive and authentic workplace. If your past experience doesn’t align perfectly, we encourage you to join our Talent Community to stay connected to additional career opportunities. Although this role is listed as full-time, if you’re in a job-share partnership, work reduced hours, or have any other flexible arrangement, please still get in touch. We will also offer reasonable adjustments to the recruitment process if required, so please let us know.

Gallagher is an affirmative action/equal opportunity employer (Minorities/Females/Veterans/Disabled)

Architecture & Strategy

• Define and implement the enterprise data architecture aligned to insurance business priorities (underwriting, claims, actuarial, finance)
• Design and optimise Snowflake-based data platforms, ensuring scalability, security, and cost efficiency
• Lead the transition from legacy policy, claims, and finance systems to modern cloud data solutions
• Establish architectural patterns supporting data domains, data products, and reusable assets

Data Modelling Skills & Experience

• Excellent understanding of conceptual, logical, and physical data modelling principles.
• Experience designing enterprise data models, reporting marts and business specific data products.
• Ability to model complex business relationships, hierarchies, and many-to-many relationships.
• Proficiency in dimensional modelling techniques including star schemas, snowflake schemas, facts, dimensions, and slowly changing dimensions (SCDs).
• Experience producing ERDs, logical data models, business data models, and data dictionaries.
• Strong knowledge of data normalization and denormalization techniques.
• Experience defining and documenting business rules, data lineage, data ownership, and metadata.
• Experience working with Master Data Management (MDM) solutions, including integrating mastered data into enterprise data models and analytical platforms.
• Understanding of data quality, reconciliation, and data governance considerations within data model design

• Previous experience as a Data Architect working in the the Insurance Industry is essential for this position.  An understanding of insurance and brokerage data domains and their interdependencies is required.
• Experience modelling data across key business subject areas including:
  • Client and customer
  • Policy lifecycle
  • Risk and coverage
  • Claims management
  • Finance, premium, commission, and brokerage transactions
  • Insurer
  • Regulatory, compliance, and conduct reporting
  • Ability to develop enterprise data models that support operational processes, management information (MI), regulatory reporting, and analytics.

• Understanding of how data flows across policy administration, claims, finance, CRM, and external market systems.
• Ability to translate complex insurance business concepts into scalable and reusable data models.
• Design and govern dbt-based transformation frameworks, including modular, testable, and well-documented models
• Establish best practices for ELT pipelines, lineage, and dependency management
• Enable self-service analytics through curated semantic and presentation layers
• Drive automation, CI/CD, and testing across the data lifecycle

• Commercial awareness of insurance value chains and drivers

• Strategic but pragmatic—able to balance architecture vision with delivery reality

• High attention to data accuracy, auditability, and compliance

• Excellent stakeholder management at senior and executive level

• Comfortable operating across hands-on delivery and architectural oversight

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