Azure Databricks Data Engineer – Insurance (Hybrid)

EXL Talent Acquisition Team; Greater London; Hybrid; GBP 70.000 - 110.000; Vollzeit

Benefits dieser Stelle

Private healthcare

Critical illness cover 4x salary

Income protection insurance

Pension

Cycle Scheme

Employee Stock Purchase Plan

Zusammenfassung

EXL is seeking an Azure Databricks Data Engineer for its Insurance portfolio in London. This hands-on role requires strong Azure and Databricks experience, plus solid Insurance domain knowledge.

You’ll design and deliver cloud-based data integration and analytics solutions, working across data engineering, modelling, and transformation initiatives. The ideal candidate will lead data engineering efforts, optimise pipelines, and contribute to data quality and governance within a forward-thinking,

Qualifikationen

• Insurance domain knowledge and data governance are essential.
• Experience leading technical delivery and teams in data engineering environments.
• Hands-on with Spark (PySpark/SparkSQL) and ETL/ELT design.
• Strong SQL, version control, and CI/CD practices are required.

Aufgaben

• Design, build, and deploy scalable data pipelines using Azure Databricks and Azure tools.
• Optimise Databricks environments for performance, cost, and security.
• Develop data integration, ETL/ELT processes and data quality frameworks.
• Translate business requirements into data models and collaborate with stakeholders.

Kenntnisse

Insurance domain knowledge

Data governance

Agile delivery

Stakeholder engagement

Tools

Azure Databricks

Azure Data Factory

Azure SQL Database

Spark PySpark

Git CI/CD

Jobbeschreibung

EXL is seeking an Azure Databricks Data Engineer for its Insurance portfolio in London. This hands-on role requires strong Azure and Databricks experience, plus solid Insurance domain knowledge.

You’ll design and deliver cloud-based data integration and analytics solutions, working across data engineering, modelling, and transformation initiatives. The ideal candidate will lead data engineering efforts, optimise pipelines, and contribute to data quality and governance within a forward-thinking,