About the Business

Quilter plc is a leading wealth management business, helping to enable brighter financial futures for every generation.

Quilter oversees £157.4billion in customer investments (as of June 2026). It has an adviser and customer offering spanning financial advice, investment platforms, multi-asset investment solutions, and discretionary fund management. The business is comprised of two segments: Affluent and High Net Worth.

Affluent encompasses the financial planning business, Quilter Financial Planning, the Quilter Investment Platform and Quilter Investors, the multi-asset investment solutions business.

High Net Worth includes the discretionary fund management business, Quilter Cheviot, together with Quilter Cheviot Financial Planning - offering a highly personalised service to private clients, charities, trustees, and professional partners. Quilter Cheviot has presence throughout the UK, Ireland and Channel Islands.

At Quilter we never stand still. Our foundations are rooted in our extraordinary expertise, which is trusted by hundreds of thousands of customers, but we have great ambitions to stay one step ahead and make an even greater difference to the people and communities we serve, including our colleagues.

Our business is transforming, continually modernising, and becoming even more customer centric. So, if you want to be bold in the pursuit of your ambitions, bring new ideas, and challenge and evolve what we do, it's the perfect time to join us

About the Role

Level: 4

Department: CDO

Location: Southampton or London

Contract type: Permanent

The role sits within the Chief Data Office (CDO) and reports to the Data Engineering Manager.

This role accelerates Quilter's data strategy by providing deep, technical leadership across one or more data domains; defining engineering standards, and delivering robust, scalable and secure solutions.

The Lead Data Engineer plays a pivotal role in enabling business value through the design, development, and continuous improvement of data products and platforms that support actionable insights across the organisation.

Working closely with engineers, architects, analysts, platform teams, and business stakeholders, the Lead Data Engineer is responsible for translating business requirements into robust technical solutions while driving engineering best practices and fostering a culture of technical excellence. The role requires deep technical expertise, strong problem-solving capabilities, and the ability to influence and guide both technical and non-technical stakeholders.

The key accountabilities for the role are as follows:

Technical Leadership & Domain Ownership

• Provide technical leadership for one or more data domains, acting as the primary engineering authority and subject matter expert.

• Define, champion, and evolve data engineering standards, patterns, and best practices to ensure robust, efficient, secure, and maintainable solutions.

• Lead solution design activities and guide the implementation of scalable data pipelines, data products, and platform capabilities.

• Review code, architecture, and engineering approaches to ensure consistency, quality, and alignment with strategic objectives.

• Remain hands-on when required, supporting the resolution of complex technical challenges and critical delivery issues.

Engineering Delivery

• Lead the technical delivery of key initiatives and ensure solutions are delivered to a high standard, meeting business requirements and engineering principles.

• Translate business and product requirements into detailed technical designs and implementation plans.

• Collaborate with Data Engineering Managers, Product Owners, Architects, and stakeholders to prioritise and deliver work effectively.

• Drive adoption of modern engineering practices including automation, testing, CI/CD, source control, observability, and infrastructure-as-code.

• Contribute to roadmap planning by identifying technical opportunities, risks, dependencies, and improvement initiatives.

Mentoring & Capability Development

• Provide coaching, mentoring, and technical guidance to data engineers across the team.

• Support the development of engineering capability through knowledge sharing, technical reviews, pair programming, and communities of practice.

• Promote a collaborative and inclusive engineering culture focused on quality, learning, and continuous improvement.

• Act as a role model for engineering excellence and professional standards.

Cross-Functional Collaboration

• Partner with product managers, analysts, data scientists, platform teams, and business

• stakeholders to understand requirements and deliver valuable outcomes.

• Work closely with architecture, platform, and governance teams to ensure solutions align with enterprise standards and strategic direction.

• Communicate technical concepts clearly to both technical and non-technical audiences.

• Influence decision-making by providing expert technical advice and recommendations.

Operational Excellence

• Promote operational stability, reliability, and performance of data products and pipelines through monitoring, alerting, automation, and incident management practices.

• Champion high standards of data quality, security, governance, and regulatory compliance.

• Identify and implement opportunities to improve platform efficiency, engineering productivity, and service resilience.

• Support root cause analysis and continuous improvement activities to enhance operational performance and service reliability.

About You

Qualifications

• Degree in a technical discipline (e.g. computer science, engineering, maths, physics) or evidence of equivalent practical experience

Knowledge

• Proven experience as a senior or lead data engineer within a complex enterprise environment, delivering large-scale data solutions.

• Strong hands-on experience designing, developing, and supporting data platforms and pipelines using Databricks within Azure.

• Experience implementing both batch and real-time data processing solutions, including event-driven and streaming architectures.

• Demonstrable experience leading the technical design and delivery of data products and platform capabilities across one or more business domains.

Experience impleme