Senior Data Engineer (Databricks)

EXL (NASDAQ: EXLS) is a global data and AI company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. Bringing together domain expertise with robust data, powerful analytics, cloud and AI to create agile, scalable solutions and execute complex operations for the world's leading corporations.

EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect, creating value from data to ensure faster decision-making and transforming operating models. Key industries include Insurance, Healthcare, Banking and Financial Services, Media, and Retail, among others.

Headquartered in New York, our team is over 60,000 strong, with more than 50 offices spanning six continents. Role Title: Databricks Data Engineer BU/Segment: Analytics / Data Management / Insurance Domain Location: London, United Kingdom (Hybrid, 3-4 days in the office) Employment Type: Permanent to start ASAP Summary of

the role

We're looking for a highly skilled Azure Databricks Data Engineer to design, develop and deliver cloud-based data integration and analytics solutions within our Insurance portfolio . You'll work across data engineering, modelling, and transformation initiatives — building scalable pipelines, optimising performance, and ensuring best practices in data quality and governance.

This is a hands-on technical role requiring strong Azure and Databricks experience, coupled with solid Insurance domain knowledge . As part of this role, you'll have the opportunity to work on high-impact Insurance data transformation programmes, collaborating with experienced data professionals in a forward-thinking, innovative environment.

You'll gain exposure to cutting-edge Azure and Databricks technologies. As part of your duties, you will be responsible for: Design, build, and deploy scalable data pipelines using Azure Databricks , Azure Data Factory , and Azure SQL Database .

Optimise Databricks environments for performance, cost, and security. Develop and maintain data integration , ETL/ELT processes, and data quality frameworks. Translate business requirements into data models, ensuring consistency and accuracy across data layers.

Work with stakeholders to deliver effective data solutions, analytics. Create technical documentation including data flow diagrams, architecture design, and test plans. Stay current with emerging data engineering and

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