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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Platform Engineer - **Company:** Moneysupermarket Group - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Automation of Tests, Cloud Computing, Code Review, Continuous Integration, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Data Sharing, Data Warehousing, Python (Programming Language), Machine Learning, Operational Data Store, Reliability Engineering, Software Engineering, SQL Databases, Machine Learning Operations, Virtual Agents, Terraform, Stream Processing, Software Version Control, Data Pipelines, Serverless Computing - **Published:** July 26, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=8e1623998b15ba28 ## About the Role * Strong software or data engineering fundamentals, including production Python and SQL. * Experience building, operating or improving cloud-based systems. * Familiarity with infrastructure-as-code, CI/CD, version control and automated testing. * Ability to reason about reliability, security, observability and 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 practical delivery workflows. Useful but not essential * Experience with GCP or AWS services such as serverless runtimes, networking, data warehouses, streaming systems or managed workflow platforms. * Experience building or configuring AI agent workflows, custom agents, tool/function calling, MCP servers, local coding-agent instructions, hooks or SDKs. * Experience with BDD/TDD, design-for-testing, or improving testability in data and platform systems. ## Description As part of the MONY Group Data Team, our goal is to drive business growth by building and maintaining data products that power analytics, financial reporting, CRM, machine learning and personalised customer experiences. We work closely with teams across the business to make data clean, reliable, secure and 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, maintain shared 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. ABOUT THE ROLE 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 help operate and evolve the platform that supports analytics, CRM, financial reporting and 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. WHAT YOU WILL BE DOING Build and operate the data platform * 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. Deliver reliable data products * Build robust, scalable data solutions that support business needs such as CRM, SEO, financial reporting and personalisation. * Stay close to the business context and apply software engineering practices to solve specific data problems. * Improve monitoring, alerting, data quality checks and observability so issues are detected and understood quickly. Improve engineering workflows with AI and automation * Identify repeated 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, hooks and tool integrations where they deliver real value. * Balance speed with security, reviewability and maintainability when introducing AI-assisted delivery patterns. Enable the wider team * Share practical learning through documentation, demos, pairing and show-and-tell sessions. * Support more junior team members through coaching, code review and clear engineering standards. * Keep an informed view of the fast-moving AI tooling landscape and recommend adoption where it solves real team problems. ## Related Videos - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Are Code Reviews Worth It? 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