Data Platform Engineer

Every day, we push beyond expectations to help millions of people save money, at a time when it’s never mattered more. Through Money Super Market , Money Saving Expert , Quidco and our B2B partnerships we supply products to more than 24 million unique monthly visitors, helping UK households to save billions of pounds a year. Can you tell this is something we’re exceptionally proud of!

Creative, collaborative, ambitious – it’s hard work. But what makes it worth it? Leaving work knowing we’ve made a difference to our customers, users, and to each other.

Put our distinct brands together with our dedicated colleagues and you’ve got a workplace with lots of personality. We’re open-minded, diverse, and love our differences. Everyone plays a part, and comes together to work hard, go beyond, and make sure everyone feels they belong.

As part of the MONY Group Data Team, our goal is to drive business growth by building andmaintainingdata products that power analytics, financial reporting, CRM, machinelearningandpersonalisedcustomer experiences. We work closely with teams across the business to make data clean, reliable,secureand accessible for decision-making.

Data & AI Engineering is a cross-functional team of engineers and scientists. We integrate with the group’s operational data stores,maintainshared data models, build AI-infused internal and external data products, and provide tools and services that help data teams handle data securely and ship with confidence.

This is a hands-on engineering role for someone who wants to build reliable data platform capability and improve how engineering work gets done.

You will helpoperateand evolve the platform that supports analytics, CRM, financialreportingand machine learning across MONY Group.

AI-assisted engineering is an important part of the role, but we do not expect candidates to arrive as experts in every agent framework or tool. We are looking for strong engineering judgement, curiosity, and the ability to apply automation responsibly to real delivery and operational problems.

You might come from data engineering, platform engineering, software engineering, SRE, analytics engineering,MLOps, or cloud infrastructure. What matters most is that you enjoy reducing toil, improving developer experience, and building secure, observable systems that other teams can depend on.

• Contribute to the design, delivery and operation of platform infrastructure using infrastructure-as-code, primarily Terraform.
• Improve CI/CD pipelines, deployment practices and platform tooling that enable data teams to self-serve safely.
• Work with security,compliance and data protection colleagues to reduce risk and improve data handling practices.

• Build robust, scalable data solutions that support business needs such as CRM, SEO, financialreportingandpersonalisation.
• Stay close to the business context and apply software engineering practices to solve specific data problems.
• Improve monitoring, alerting, data qualitychecksand observability so issues are detected and understood quickly.

• Identifyrepeated or high-friction engineering tasks and turn them into reliable automated or AI-assisted workflows.
• Help shape team practices for coding agents, prompts, local instructions, skills,hooksand tool integrations where they deliver real value.
• Balance speed with security,reviewability and maintainability when introducing AI-assisted delivery patterns.

• Share practical learning through documentation, demos,pairingand show-and-tell sessions.
• Support more junior team members through coaching, codereviewand clear engineering standards.
• Keep an informed view of the fast-moving AI tooling landscape and recommend adoption where it solves real team problems.

• Strong software or data engineering fundamentals, including production
  
  Python and SQL.
• Experience building,operatingor improving cloud-based systems.
• Familiarity with infrastructure-as-code, CI/CD, versioncontroland automated testing.
• Ability to reasonaboutreliability, security,observabilityand operational support.
• Experience working with technical and non-technical stakeholders and communicating clearly.
• Curiosity about AI-assisted engineering and automation, with an interest in applying these tools to…