Analytics Engineer

Analytics Engineer

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

At a Glance

  • Tasks: Design and build data models using AI tools to drive impactful business decisions.
  • Company: Join Zego, a forward-thinking insurance company revolutionising the industry.
  • Benefits: Enjoy competitive salary, private medical insurance, share options, and generous holiday allowance.
  • Other info: Flexible hybrid working model and a culture that celebrates diversity and collaboration.
  • Why this job: Be part of a dynamic team that values your growth and embraces AI innovation.
  • Qualifications: 1-3 years experience in analytics engineering with strong SQL skills.

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

At Zego, we understand that traditional motor insurance holds good drivers back. It's too complicated, too expensive, and it doesn't reflect how well you actually drive. Since 2016, we have been on a mission to change that by offering the lowest priced insurance for good drivers.

Overview of Team

The Data team at Zego partners with the business to maximise the value of data. Through collaborative engineering and analytics, we ensure our teams are equipped with relevant and reliable insights to drive fast, confident and high-impact decisions. We're a small, dynamic team responsible for all aspects of data — availability, quality, integration, problem formulation, success metrics, reporting, and analytics. We take an AI-First approach: AI is now central to how we work, and we focus less on hand-writing code and more on framing problems, specifying intent, and owning the trust infrastructure (testing, contracts, observability) that the business relies on.

About the Role

We're looking for an Analytics Engineer who's genuinely excited about how this craft is changing. The way we build is shifting: AI tools now handle a lot of the heavy lifting of writing SQL and boilerplate, which means the job is increasingly less about typing code and more about understanding the business problem, specifying what "good" looks like, and making sure what we ship is correct and trustworthy.

In practice, that means you'll design and build data models with the support of AI-assisted workflows, and you'll own a growing share of the testing, data contracts, and observability that let the rest of the business rely on our data with confidence. You'll work closely with senior engineers and stakeholders, with plenty of room to grow your technical depth and take on more ownership over time. You'll have a solid technical foundation, a natural curiosity for data, and a healthy instinct to question whether a number is actually right — not just whether a query ran.

What You Will Be Doing

  • Data Modelling & Engineering (AI-assisted): Work with stakeholders to understand business needs and translate them into clear, well-scoped requirements. Build and maintain robust data models and exposures in dbt, Snowflake, and Looker — using AI-assisted development to move faster, spending less time hand-writing boilerplate and more time specifying intent, reviewing, and refining. Read, debug, and critically review SQL (including AI-generated code), so we ship models we can trust. Document modelling decisions, trade-offs, and outcomes clearly. Wrangle and integrate data from multiple third-party sources (e.g. Amplitude, Segment, Google Ads).
  • Data Quality, Trust & Operations: Help build and maintain the "trust infrastructure" — tests, data contracts, and observability — that lets the business depend on our models. Ensure quality, reliability, and stability across data models and pipelines. Create secure, efficient data shares for external partners (e.g. S3, SFTP, Snowflake Data Sharing). Contribute to the continuous improvement of our data platform, tooling, and ways of working — including how we use AI in our workflows.
  • Stakeholder Enablement: Support business users across the company to promote a culture of data-driven decision-making. Help translate business questions into well-designed data solutions and metrics. Help enable and maintain self-service capabilities within our BI tools.

About You

You'll have around 1–3 years' experience as an Analytics Engineer or in a similar role. You'll have solid SQL skills — comfortable reading, writing, debugging, and critically reviewing queries (including AI-generated ones); experience with dbt and/or Looker is a plus. You'll have some familiarity with modern data platforms (e.g. Snowflake, dbt, AWS, GCP, Looker). You'll have experience with version control tools such as Git. You'll ideally have some exposure to Python for data or analytics engineering tasks. You'll have a meticulous eye for detail and strong problem-solving instincts — you care about whether the answer is correct, not just whether the code runs. You'll be genuinely excited about AI and how it changes our work — already using (or quickly building confidence with) AI tools to work smarter, and taking ownership of staying ahead. This is central to how our team works, not a nice-to-have. You'll have commercial curiosity — an interest in the "why" behind the numbers and the ability to connect data work to business outcomes. Experience in the insurance sector is a plus.

What’s it Like to Work at Zego?

Joining Zego is a career-defining move. People go further here, reaching their full potential to achieve extraordinary things. We’re spread throughout the UK and Europe, and united by our drive to get things done. We’re proud of our company and our culture - a friendly and inclusive space where we can lift each other up and celebrate our wins every day. Together, we’re setting the bar higher, delivering exceptional work that makes a difference. Our people are the most important part of our story, and everyone here plays a role. There’s loads of room to learn and grow, and you’ll get the freedom to steer your career wherever you want. You’ll work alongside a talented group who embrace each other’s differences and aren’t afraid of a challenge. We recognise our achievements, learn from our mistakes, and help each other to be the best we can be. Together, we’re making insurance matter.

How We Work

We believe that teams work better when they have time to collaborate and space to get things done. We call it Zego Hybrid. While some of our team choose to come into our central London office once a week, we’re flexible - some people prefer being in once a month or even quarterly. It’s all about finding the right balance between collaborative face time and focused home-working, so we can achieve great results while maintaining a healthy work-life balance.

Our Approach to AI

We believe in the power of AI to meaningfully improve how we work - helping us move faster, think differently, and focus on what matters most. At Zego, we encourage people to stay curious and intentional about how AI is leveraged in their work and teams to drive practical impact every day. This is your chance to do the most meaningful work of your career - and we’ll provide you with the tools, support, and freedom to do it well.

Benefits

We reward our people well. Join us and you’ll get a market-competitive salary, private medical insurance, company share options, generous holiday allowance, and a whole lot of wellbeing benefits. We also offer an annual flexible hybrid working contribution, which you can use to support with your travel to the office or towards your own personal development. And that’s just for starters!

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, or disability status.

Zego

Contact Details:

Zego Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Analytics Engineer

Get Involved in Data Science Meetups

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Show Off Your Projects

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Zego.

Apply Directly through Our Website

When you find a suitable opening like Analytics Engineer at Zego, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Analytics Engineer

SQL
Data Modelling
dbt
Snowflake
Looker
AI-assisted Development
Data Integration

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Zego, 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 Zego. 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 Zego

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!

Showcase Your Projects

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

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Zego!

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.