At a Glance
- Tasks: Design and build AI-augmented workflows for analytics engineering tasks.
- Company: Join a dynamic team at MONY Group, helping millions save money.
- Benefits: Enjoy up to 27 holidays, a bonus scheme, and work-from-anywhere options.
- Other info: Mentorship and personal growth opportunities with access to 16,000 courses.
- Why this job: Be at the forefront of AI in data engineering and make a real impact.
- Qualifications: Strong SQL skills, experience with dbt, and a passion for automation.
The predicted salary is between 60000 - 75000 £ 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. 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 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 a Senior 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
- AI-First Workflow Design: 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.
- Analytics Engineering: 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.
- Enablement & Engineering Practice: 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
- Essential: 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.
- Desirable: 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
- Bonus scheme
- Digital Doctor on demand
- 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 understand that job adverts only say so much and you’re likely to have a lot of questions. If you’d like to know more before applying such as more on hybrid working, salary, our parental leave policy etc, please just let us know, and we’ll be happy to help. You can contact the recruiter for this role, Kim at kim.richards@monygroup.com.
We believe that success isn’t solely defined by ticking boxes on a skills checklist. We encourage your application, so we can discover your skills and experience that will help you succeed in this role.
Analytics Engineer in London employer: MONY Group
Contact Detail:
MONY Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at events. Ask them about their experiences and the company culture. This not only gives you insider info but also shows your genuine interest in the role.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL and data modelling skills. Be ready to discuss how you've used AI tools in your past projects. We want to see your hands-on experience and how you can bring that to our team!
✨Tip Number 3
Showcase your problem-solving skills during interviews. Think of examples where you automated tasks or improved workflows. We love candidates who can think outside the box and push boundaries, just like we do at StudySmarter!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining our awesome team and making a difference for our users.
We think you need these skills to ace Analytics Engineer in London
Some tips for your application 🫡
Show Your Passion for Data: When you're writing your application, let your enthusiasm for data and analytics shine through! We love seeing candidates who are genuinely excited about using data to make a difference. Share any personal projects or experiences that highlight your passion.
Tailor Your Application: Make sure to customise your application to reflect the specific skills and experiences mentioned in the job description. We want to see how your background aligns with our needs, so don’t be shy about showcasing your expertise in SQL, dbt, and AI tooling!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on communicating your experience and skills effectively. Remember, we’re looking for someone who can explain complex concepts simply!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at MONY Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in SQL, dbt, and BigQuery. Brush up on your data modelling techniques too! Being able to discuss your hands-on experience with these tools will show that you’re not just familiar with them, but that you can leverage them effectively in real-world scenarios.
✨Showcase Your AI Knowledge
Since this role is all about pushing the boundaries of AI in analytics, be prepared to discuss your experience with AI coding agents. Share specific examples of how you've used tools like GitHub Copilot or Claude Code to automate workflows and improve efficiency.
✨Communicate Clearly
You’ll need to explain complex concepts to both technical and non-technical colleagues. Practice articulating your thoughts on AI-driven approaches and data governance in a way that’s easy to understand. This will demonstrate your strong communication skills and ability to collaborate across teams.
✨Be Ready to Discuss Automation
Think about repetitive tasks you’ve encountered in your previous roles and how you approached automating them. Be ready to share your ideas on what could be automated in the new role and how that would benefit the team. This shows initiative and a forward-thinking mindset!