Azure Data Architect

Location: Greater London

Job Title:

Data Architect – Azure Databricks / Azure Data Factory For London Market Insurance Exp Required – 10 years Plus

Location:

London About the Job you are considering:

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.

Key Responsibilities:

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, Dev Ops, and business teams.

Define CI/CD, Dev Ops, 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.

Mandatory Skills 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 Gen
2.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…