Data Engineer

At Verisk, we empower businesses around the world with data, analytics, technology, and deep domain expertise. Our solutions help customers manage risk, improve performance, and make confident decisions in complex environments.

Within Verisk General Insurance UK, we provide market-leading data and analytics solutions that support insurers, brokers, and industry partners. Our datasets span property, motor insurance, fraud prevention, and claims, helping customers better understand risk and improve outcomes.

We're looking for a Data Engineer to join our Norwich-based team and play a key role in delivering customer-facing data solutions. This is an opportunity to work directly with valuable insurance datasets, lead proof-of-concept initiatives, and help shape the way data is delivered, automated, and scaled across the business.

Why this role?

This role offers a unique combination of data engineering, customer impact, and technical ownership.

You'll be trusted to lead underwriting proof-of-concept projects that help customers evaluate the value of Verisk data before making commercial decisions. Your work will directly influence customer outcomes, product adoption, and future business opportunities.

You'll also have the opportunity to improve and automate existing processes, work with modern cloud technologies, and expand your expertise across a broad range of data engineering activities.

What makes this role different:

• Own customer proof-of-concept projects from end to end

• Work with large-scale property and insurance datasets used throughout the industry

• Partner with both technical teams and non-technical business stakeholders

• Help modernize and automate existing workflows using AWS and Python

• Gain exposure to multiple areas of the data engineering function through cross-training

• Join a collaborative team where communication, initiative, and problem-solving are highly valued

About the team

You'll join a team primarily made up of Data Analysts alongside an experienced Data Engineer. The role will work closely with both groups, supporting underwriting databases, sharing knowledge, and contributing to broader data engineering initiatives.

While you'll take primary ownership of proof-of-concept activities, you'll also have the opportunity to learn other areas of the team's work, contributing to a collaborative environment where knowledge sharing and cross-training are encouraged.

#LI-SD2 #LI-Hybrid

• Leading customer underwriting proof-of-concept (POC) projects from initial request through final delivery
• Working with customer-provided address data and matching it to unique reference identifiers
• Extracting, transforming, and delivering risk intelligence data including factors such as flood, fire, and burglary risk
• Producing clear data outputs and supporting documentation, including data dictionaries, that allow customers to easily evaluate results
• Investigating data-quality questions, coverage issues, and customer queries to ensure confidence in delivered outputs
• Using SQL and Python to extract, manipulate, validate, and prepare complex datasets
• Collaborating with internal stakeholders to understand evolving business and customer requirements
• Supporting and enhancing underwriting data platforms and associated data processes
• Working alongside the wider team to reduce single-person dependencies through knowledge sharing and cross-functional support
• Identifying opportunities to automate manual activities within the POC lifecycle
• Leveraging AWS technologies to improve scalability, efficiency, and repeatability of data processes
• Contributing ideas and recommendations that improve team effectiveness, data quality, and customer experience
• Maintaining high-quality technical documentation and providing clear project updates to stakeholders

We're looking for someone who combines strong technical capability with curiosity, initiative, and excellent communication skills.

You'll be comfortable working independently, solving problems, and explaining technical concepts to audiences with varying levels of technical knowledge.