Level

RELX

Manager Software Engineering

AI in this role

databricks

Are you a strategic technology leader who is passionate about modernising data platforms, leading high-performing teams, and delivering impactful data solutions at scale?

Do you thrive on driving cloud transformation, strengthening data governance, and advancing AI adoption while partnering with stakeholders across a global organisation?

About the Business

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle, all while reducing risk. You can learn more about LexisNexis Risk at https://risk.lexisnexis.com/insurance.

About our Team:

The UK&I Data Engineering organization designs, builds, validates, governs, and operates data products supporting Business Services and Insurance solutions. The team is responsible for data onboarding, engineering delivery, cloud modernization, data governance, production operations, quality assurance, and regulatory compliance while partnering closely with Product, Architecture, Operations, Security, and Analytics teams.

About the Role

As Head of Data Engineering, you will provide leadership, strategic direction, and operational oversight for the UK&I Data Engineering team. You will play a key role in driving cloud modernisation, strengthening governance and security practices, accelerating AI adoption, and ensuring the successful delivery of business-critical data products that support business growth and customer outcomes.

Working across global teams and stakeholders, you will balance delivery excellence with long-term technology strategy, fostering a culture of innovation, collaboration, and continuous improvement.

Responsibilities

  • Lead and support data engineers, ensuring clear priorities and consistent delivery
  • Build a culture of accountability, collaboration, continuous improvement, and innovation
  • Support career development, succession planning, talent acquisition, and workforce planning
  • Foster knowledge sharing and engineering excellence practices across US and UK teams
  • Oversee delivery of data products, ingestion pipelines, reporting solutions, and customer-facing capabilities
  • Lead cloud migration and modernisation initiatives leveraging Azure, Databricks, cloud-native services, and modern data architectures
  • Ensure adherence to data governance, privacy, security, compliance, and regulatory requirements
  • Partner with Product, Analytics, Architecture, Operations, and Business Leaders to deliver scalable technical solutions

Requirements

  • Experience in Data Engineering, Analytics Engineering, Data Platforms, or related technology disciplines
  • Leadership experience managing technical teams
  • Strong expertise in modern data engineering practices, data architecture, and large-scale data platforms
  • Experience delivering cloud-based solutions, preferably using Azure technologies
  • Strong understanding of data governance, privacy, security, compliance, and risk management requirements
  • Experience leading strategic initiatives and complex cross-functional programs
  • Strong communication, stakeholder management, and organisational leadership skills
  • Demonstrated ability to balance delivery execution with long-term technology strategy

Risk benefit statement

Learn more about the LexisNexis Risk team and how we work here

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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How we rate this

Manager Software Engineering at RELX rates 15 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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