Data Engineer II
A UK-based data engineer role at LexisNexis Risk Solutions focused on building and maintaining data products for the insurance lifecycle. Day-to-day involves data profiling, validation, and quality management, plus designing scalable data pipelines using SQL, Java/J2EE, JavaScript, C/C++, .NET, and HPCC, with growing emphasis on AI-assisted automation.
- Compensation
- Not disclosed
- Location
- United Kingdom
- Work setup
- Not specified
- Seniority
- Middle
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Experience in Data Management, Data Engineering or related technical data role
- Strong data manipulation, profiling, validation and data quality practices
- Experience with data models, data requirements and maintainable solution designs
- Experience with SQL, Java/J2EE, JavaScript, C/C++, .NET, HTML/XML, HPCC, Windows or Unix
- Understanding of software engineering practices (testing, code reviews, maintainability) and development methodologies (Agile or Waterfall)
- Strong analytical and problem-solving abilities with option assessment and recommendation
- Clear communication, attention to detail and willingness to learn new technologies including AI and automation
Full description
Overview
As a Data Engineer, you will design and maintain reliable data solutions to enable high-quality data products for the insurance lifecycle. You’ll start with data management tasks—profiling, validation and quality control—and grow into broader data engineering ownership. You’ll partner with technical teams and stakeholders to translate requirements into scalable solutions that improve data quality, operational efficiency and customer outcomes. You will explore automation and AI-assisted methods to boost productivity and delivery. This role offers meaningful impact by elevating data-driven decision making in the insurance domain.
Responsibilities
- Own data transfers and components, including collection, transfer, and contributor/customer setup, with maintainability in mind
- Collaborate with technical teams and stakeholders to convert data and product requirements into effective solutions
- Design, develop, test and maintain repeatable, scalable data engineering solutions following best practices
- Evaluate approaches and recommend options balancing delivery speed, data quality, testing, and maintainability
- Perform Data Management activities: profiling, validation, quality management, and issue investigation/resolution
- Troubleshoot data engineering issues, identify root causes and implement sustainable fixes
- Identify opportunities for automation, including AI-assisted engineering and intelligent automation
- Contribute to code reviews, specifications, database/workflow management, and adoption of new technologies
Key requirements
- Experience in Data Management, Data Engineering or related technical data role
- Strong data manipulation, profiling, validation and data quality practices
- Experience with data models, data requirements and maintainable solution designs
- Experience with SQL, Java/J2EE, JavaScript, C/C++, .NET, HTML/XML, HPCC, Windows or Unix
- Understanding of software engineering practices (testing, code reviews, maintainability) and development methodologies (Agile or Waterfall)
- Strong analytical and problem-solving abilities with option assessment and recommendation
- Clear communication, attention to detail and willingness to learn new technologies including AI and automation
- clear communication
- attention to detail
- problem-solving
- SQL
- Java/J2EE
- JavaScript