Analytics Engineer

Analytics Engineer

Full-Time 50000 - 70000 £ / year (est.) Home office (partial)
M

At a Glance

  • Tasks: Design and build AI-augmented workflows for analytics engineering tasks.
  • Company: Join a leading tech company helping millions save money.
  • Benefits: Up to 27 holidays, work from anywhere, and financial coaching.
  • Other info: Embrace personal growth with dedicated training and mentorship opportunities.
  • Why this job: Be at the forefront of AI in data engineering and make a real impact.
  • Qualifications: Strong SQL skills, dbt experience, and familiarity with AI coding agents.

The predicted salary is between 50000 - 70000 £ per year.

Every day, we push beyond expectations to help millions of people save money, at a time when it’s never mattered more. Through MoneySuperMarket, MoneySavingExpert, 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. 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 and maintaining data products that power analytics and personalised customer experiences. We work closely with teams across the business to ensure that data is clean, reliable, and accessible for data-driven decision-making. In Data AI Engineering we are a cross‑functional team of engineers and scientists, responsible for data integration with the group’s operational data stores, providing a common data model which serves as a source of truth for financial reporting, analytics and CRM, AI‑infused applications for internal and external data products, and the tools and services used by other data teams to improve their secure data handling practices and development experience.

Our team has adopted coding agents and AI tooling across the board – but like most teams, we’re caught in the tension between day‑to‑day delivery and investing the time to truly unlock what AI can do for our workflows. This role exists to break that deadlock. As an Analytics Engineer, you will be the driving force behind making our analytics engineering workflows AI‑first. You’ll bring a strong analytics engineering foundation – you know dbt, BigQuery, and data modelling inside out – but your primary mission is to tenaciously push the boundaries of what we can automate. Data pipeline maintenance, bug fixes, refactors, governance, testing: your goal is to systematically make these faster, cheaper, and increasingly autonomous, freeing the team to focus on the high‑value feature builds that move the business forward. You’ll work hands‑on as an analytics engineer while simultaneously building the AI‑augmented workflows, tooling, and practices that multiply the output of the entire team. If you’re the kind of engineer who sees a repetitive task and immediately thinks about how to make an agent do it, this role is for you.

WHAT YOU WILL BE DOING

  • Design, build, and iterate on AI‑augmented workflows for analytics engineering tasks, pushing well beyond basic autocomplete into agentic automation.
  • Build and maintain coding agent customisations (e.g. AGENTS.md, skills, MCP servers, custom hooks) that encode our team’s domain knowledge and standards.
  • Build and maintain scalable data models using BigQuery SQL and dbt fusion.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver robust, production‑ready solutions.
  • Develop and maintain data quality standards and contribute to data governance practices.
  • Champion AI‑first practices across the data team, coaching engineers on effective use of coding agents and AI tooling.
  • Contribute to and improve our CI/CD pipelines (GitHub Actions), infrastructure‑as‑code (Terraform), and deployment practices (Cloud Run).
  • Stay relentlessly up to date on the fast‑moving AI tooling landscape and advocate for adoption where it delivers genuine value.

WHAT WE LOOK FOR

  • Strong SQL and solid understanding of data modelling (e.g. Kimball, wide/flat).
  • Professional dbt experience – you’ve built and maintained production dbt projects.
  • Experience with BigQuery or another cloud data warehouse.
  • Demonstrable, hands‑on experience using AI coding agents (e.g. Claude Code, Cursor, GitHub Copilot) to meaningfully accelerate your own work – not just autocomplete, but agentic workflows.
  • Self‑directed and tenacious – this role requires someone who will push forward without needing to be told what to automate next.
  • Strong communication skills – you can explain AI‑driven approaches to both technical and non‑technical colleagues and bring people along.
  • Comfortable with version control (Git & GitHub), CI/CD concepts, and collaborative development workflows.
  • Experience building or configuring AI agent workflows (e.g. custom agents, tool/function calling, MCP servers, Claude Agent SDK).
  • Familiarity with Terraform, Docker, Cloud Run, or similar infrastructure tooling.
  • Experience writing Airflow DAGs for data orchestration.
  • Exposure to Python for scripting and automation.
  • Familiarity with GitHub Actions or similar CI/CD platforms.
  • Experience with data governance and data quality frameworks.
  • Tableau or other data visualisation tools.

PERSONAL GROWTH

You’ll be at the forefront of a genuine shift in how data engineering teams work – the skills and experience you build here will be in extraordinary demand. Work with one of the largest customer databases in Europe, holding records for over 30 million unique customers. Learn and grow by working with the latest technology and services from Google, and AI tools from all the leading providers. Training, sharing knowledge, and best practice are integral to our team ethos – Moneysupermarket make learning and personal growth a priority, with dedicated time and budget for your development every year.

WHAT REWARDS ARE ON OFFER

  • Up to 27 holidays + bank holidays.
  • Pension up to 6% employer contribution.
  • Work from anywhere scheme – 2 weeks per year.
  • Financial coaching.
  • Mental health platform access.

HOW WE’LL INVEST IN YOU

We’re invested in your development. Expect mentorship, training, and opportunities to expand your skill set, including access to your own individual LinkedIn Learning license with access to over 16,000 courses. At MONY Group, we believe in the strength of diversity and see inclusion as a strategic advantage. Our values guide us in creating a workplace where fairness and equity is a reality for all. We’re committed to minimising systemic bias and creating a level playing field for all candidates. Contact us for reasonable accommodations in the application process, no need to disclose your disability or condition, just specify your needs. Unsure what to ask for? We can guide you through available accommodations. We encourage your application, so we can discover your skills and experience that will help you succeed in this role.

Analytics Engineer employer: MONY Group plc

At MONY Group, we pride ourselves on being an exceptional employer that champions creativity, collaboration, and personal growth. Our Analytics Engineers play a pivotal role in driving innovation within our data team, supported by a culture that values diversity and inclusion, alongside comprehensive benefits such as generous holiday allowances, financial coaching, and dedicated development budgets. Join us in a dynamic environment where your contributions directly impact millions of customers while you advance your skills with cutting-edge technology and AI tools.

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Contact Details:

MONY Group plc Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Analytics Engineer

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Apply Directly through Our Website

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We think you need these skills to ace Analytics Engineer

SQL
Data Modelling
dbt
BigQuery
AI Coding Agents
Automation
Data Governance

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at MONY Group plc, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at MONY Group plc. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at MONY Group plc

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

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Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.