
MONY Group
Analytics Engineer
Salary
Competitive salary
Work type
Onsite
Level
senior
Category
Data Engineering
About the role
About us
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.
Why join the data engineering team?
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.
Purpose of the role
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.
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.
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.
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MONY Group
Analytics Engineer
Salary
Competitive salary
Work type
Onsite
Level
senior
Category
Data Engineering
About the role
About us
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.
Why join the data engineering team?
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.
Purpose of the role
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.
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.
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.