Data Engineer

As a Data Engineer at Verisk in Norwich, you will own customer-facing data solutions and lead underwriting proof-of-concept initiatives. You will work with large-scale insurance datasets to deliver scalable, automated data processing using AWS and Python. You’ll collaborate with technical and business stakeholders to refine requirements and improve data workflows, impacting product adoption and customer outcomes. This role offers hands-on ownership of POC projects and opportunities to broaden your data engineering capabilities in a supportive, cross-functional environment. You will help shape how data is delivered and understood across the business, delivering measurable value for insurers,3

• competitive compensation
• medical coverage
• life insurance
• pension plans
• paid time off
• career development and well-being initiatives

• Lead customer underwriting POC projects from request through delivery
• Work with customer-provided address data and match to reference identifiers
• Extract, transform, and deliver risk intelligence data (flood, fire, burglary, etc.)
• Produce outputs and documentation (data dictionaries) for easy evaluation
• Investigate data-quality questions and coverage issues to ensure confidence
• Use SQL and Python to manipulate and validate complex datasets
• Collaborate with internal stakeholders to align with evolving requirements
• Support and enhance underwriting data platforms and processes
• Promote knowledge sharing to reduce single-person dependencies
• Identify opportunities to automate manual POC activities
• Leverage AWS to improve scalability and repeatability
• Contribute ideas to improve team effectiveness, data quality, and customer experience
• Maintain high-quality technical documentation and provide stakeholder updates

• Strong SQL skills for querying and manipulating large datasets
• Strong Python experience in a data engineering environment
• Experience building, maintaining, or optimizing data pipelines
• Experience with AWS data engineering technologies
• Understanding of data quality, validation, and governance
• Strong analytical and problem-solving abilities
• Excellent attention to detail
• Effective communication with technical and non-technical stakeholders
• Proactive approach to process improvements
• Ability to manage priorities in a fast-paced setting

• communication
• initiative
• problem-solving
• SQL
• Python
• AWS data engineering technologies