Azure Data Architect

We are looking for an experienced Data Architect with strong expertise in Azure Databricks, Azure Data Factory, Azure Data Lake, Delta Lake, data modelling, data governance, and cloud data architecture, along with domain experience in London Market Insurance. The candidate will be responsible for defining and delivering scalable data architecture solutions for insurance transformation programmes covering underwriting, claims, policy administration, bordereaux, delegated authority, premium processing, regulatory reporting, reinsurance, analytics, and data migration. The ideal candidate should have strong hands-on architecture experience in Azure-based data platforms and should be able to work closely with business stakeholders, enterprise architects, solution architects, data engineers, insurance SMEs, vendors, and delivery teams Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time., Define end-to-end data architecture for Azure-based data platforms using Azure Databricks, Azure Data Factory, ADLS Gen2, Delta Lake, Azure Synapse, and Power BI. Design scalable and secure lakehouse architecture using bronze, silver, and gold data layers. Lead architecture and design for data ingestion, transformation, curation, data marts, reporting, and analytics solutions. Create high-level and low-level data architecture documents, data flow diagrams, integration architecture, and data platform blueprints. Define architecture patterns for batch, incremental, real-time, and API-based data ingestion. Design reusable data ingestion and transformation frameworks using ADF and Databricks. Define data models for London Market Insurance data including policy, claims, premium, broker, bordereaux, delegated authority, reinsurance, exposure, and regulatory reporting data. Work with business analysts and insurance SMEs to understand London Market business processes and translate requirements into data architecture. Define standards for data modelling, source-to-target mapping, data quality, reconciliation, metadata, lineage, and auditability. Design data governance, security, access control, and compliance frameworks for insurance data. Support cloud migration, data warehouse modernisation, reporting transformation, and legacy system decommissioning initiatives. Review technical designs, data models, ETL/ELT pipelines, and engineering implementation. Provide architectural guidance to data engineers working on Azure Databricks, ADF, PySpark, SQL, and Delta Lake. Collaborate with enterprise architecture, solution architecture, security, infrastructure, DevOps, and business teams. Define CI/CD, DevOps, deployment, monitoring, and operational support architecture for data platforms. Identify performance, scalability, reliability, and cost optimisation opportunities across Azure data services. Support governance forums, architecture review boards, design authority meetings, and client stakeholder workshops., London Market Insurance operating model Specialty insurance and commercial insurance Broker, carrier, managing agent, and syndicate data flows Underwriting data architecture Claims data architecture Policy administration data Premium and claims accounting Bordereaux processing Delegated authority and binder data Coverholder data Exposure management Reinsurance data Regulatory and compliance reporting Financial and management reporting Blueprint Two / London Market modernisation data initiatives Azure Architecture Skills Expected Candidate should have strong knowledge of the following Azure components: Azure Databricks Lakehouse architecture Databricks notebooks, jobs, workflows, clusters Delta Lake optimisation Unity Catalog, if applicable Databricks SQL, if applicable Cluster sizing and cost optimisation Security and access control patterns Azure Data Factory Pipeline orchestration Linked services and datasets Integration runtime Parameterised pipelines Triggers and scheduling Error handling and retry patterns Metadata-driven ingestion frameworks Monitoring and operational support Azure Data Lake / Storage ADLS Gen2 architecture Landing, raw, curated, and consumption zones Folder hierarchy and naming standards Partitioning strategy File format standards Data retention and archival strategy Azure Governance and Security Azure Key Vault Managed Identity Azure RBAC Storage ACLs Private endpoints Data masking Encryption at rest and in transit Logging, monitoring, and audit controls Data Architecture Responsibilities Define conceptual, logical, and physical data models. Design canonical data models for insurance entities. Define data domains such as policy, claims, party, broker, premium, risk, exposure, and reinsurance. Define source-to-target mapping standards. Establish data quality rules and validation patterns. Define metadata and lineage requirements. Design reusable data ingestion frameworks. Define data retention, archival, and purge strategies. Define master and reference data management approach. Design reporting and analytics data marts. Define semantic layer and consumption patterns for BI tools. Review and approve data engineering designs and implementation. We are a Disability Confident Employer: Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government's Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:

• Declare they have a disability, and
• Meet the minimum essential criteria for the role.

Do you have experience in Unity?, Strong experience as a Data Architect or Senior Data Architect. Strong hands-on experience with Azure Databricks. Strong architecture and implementation experience with Azure Data Factory. Strong understanding of Azure Data Lake Storage Gen2. Strong experience with Delta Lake, lakehouse architecture, and medallion architecture. Excellent knowledge of data modelling, dimensional modelling, canonical data models, and enterprise data models. Strong experience in designing ETL/ELT data pipelines. Good understanding of PySpark, Spark SQL, Python, and SQL. Strong knowledge of data warehouse, data lake, data mart, and semantic layer architecture. Experience in defining data quality, data validation, reconciliation, audit, and exception handling frameworks. Experience with data governance, metadata management, data lineage, data catalogue, and data privacy controls. Experience with Azure security concepts including Managed Identity, Azure RBAC, Key Vault, ACLs, private endpoints, and encryption. Experience with CI/CD and DevOps practices using Azure DevOps, Git, ARM templates, Bicep, or Terraform. Strong stakeholder management, communication, presentation, and documentation skills. Ability to lead architecture discussions with business, technology, and senior client stakeholders. London Market Insurance Domain Experience The candidate should have exposure to one or more of the following areas

Capgemini ist einer der weltweit führenden Anbieter von Management- und IT-Beratung, Technologie-Services und Digitaler Transformation. Als ein Wegbereiter für Innovation unterstützt das Unternehmen seine Kunden bei deren komplexen Herausforderungen rund um Cloud, Digital und Plattformen.