Data Engineer II: AI-Driven Data Pipelines

Women in Data®; England; On-site; GBP 65,000 - 90,000; Full time

Job summary

LexisNexis Risk Solutions in the UK is hiring a Data Engineer to design, develop and support reliable data solutions that improve data quality for insurance applications. You will drive data profiling, validation and quality management while growing into broader data engineering ownership.

Collaborating with technical teams and business stakeholders, you will translate requirements into scalable, maintainable data solutions, enhancing data quality and operational efficiency across the insurance

Qualifications

• Experience in Data Management, Data Engineering or related data role.
• Knowledge of data profiling, validation and data quality practices.
• Experience with data models and maintainable data solution designs.
• Understanding of testing, code reviews and agile or waterfall methodologies.
• Strong analytical skills and clear communication; interest in AI-assisted automation.

Responsibilities

• Own data transfers and components from collection to setup with maintainability.
• Translate data requirements into scalable data solutions with stakeholders.
• Design, develop, test and maintain data engineering solutions using coding practices.
• Evaluate approaches balancing delivery, data quality, testing and maintainability.
• Perform Data Management activities: profiling, validation, quality management and issue resolution.
• Troubleshoot data engineering issues, identify root causes and implement fixes.
• Identify opportunities for automation and AI-assisted engineering to boost productivity.

Skills

Data Management

Data Engineering

Data Quality

Data Modeling

Software Eng Practices

Testing

Agile/Waterfall

Analytical Thinking

Communication

AI Automation

Job description

LexisNexis Risk Solutions in the UK is hiring a Data Engineer to design, develop and support reliable data solutions that improve data quality for insurance applications. You will drive data profiling, validation and quality management while growing into broader data engineering ownership.

Collaborating with technical teams and business stakeholders, you will translate requirements into scalable, maintainable data solutions, enhancing data quality and operational efficiency across the insurance