Analytics Engineer

Zopa
Zopa

This job is no longer accepting applications

See open jobs at Zopa.See open jobs similar to "Analytics Engineer" Runa Capital.

Data Science

London, UK

Posted on Feb 19, 2026
Our Story
Hello there. We’re Zopa.
We started our journey back in 2005, building the first ever peer-to-peer lending company. Fast forward to 2020 and we launched Zopa Bank. A bank that listens to what our customers don’t like about finance and does the opposite. We’re redefining what it feels like to work in finance. Our vision for a new era of banking puts people front and centre — we’ve built a business that empowers everyone to aim high, every day, to move finance forward. Find out more about our fantastic offerings at Zopa.com!
We’re incredibly proud of our achievements and none of it would be possible without the amazing team here. It’s not just industry awards we’re winning, we’ve also been named in the top three UK’s Most Loved Workplaces.
If you embrace unconventional challenges, are unafraid to think differently and are driven to make an outsized impact, you’ll thrive here at Zopa, so join us, and make it count. Want to see us in action? Follow us on Instagram @zopalife
The team
The Analytics Engineering team is a key part of the broader Data Team within the Technology division. We’re growing and excited to welcome a new Analytics Engineer to join us! Our mission is to transform data into actionable insights, empowering analytics, product, finance, and risk teams to extract the value and information they need.
At Zopa, we’re committed to leveraging data to make smarter decisions for our customers. As an Analytics Engineer, you’ll dive into your domain, build a deep understanding of the data, and create high-quality data products. These products will be well-structured, reliable, and incorporate robust controls and quality checks using our selected tools.
In line with Zopa’s strong focus on autonomy and empowerment, you’ll take ownership of the daily operation of our data marts. This includes resolving issues, escalating when necessary, and ensuring smooth operations. Beyond technical responsibilities, you’ll collaborate closely with stakeholders to share your data knowledge and expertise. Additionally, you’ll support the team by conducting code reviews and validating data, ensuring our work meets the highest standards.
This role offers a dynamic environment where you can make a real impact while contributing to a culture of excellence and collaboration.

A day in the life:

  • You would report directly into the Head of Analytics Engineering
  • You'll collaborate with stakeholder teams to identify customer needs and deliver effective solutions that generate value for the business
  • You'll model raw data into clean, tested & reusable datasets enabling analysts and other stakeholders to understand and use data more effectively
  • You'll take ownership of existing data assets and identify ways to simplify and optimise them
  • You'll develop good relationships with product teams to understand the changes that are coming and how this might impact the processes that you own
  • You'll make your data sets a wonderful experience to use and support by providing great documentation and robust quality checks
  • You would get involved in troubleshooting and investigation of issues, liaising across teams to find solutions
  • You would provide input into improving how the team works and how to improve our processes, standards, and best practices to improve the quality and consistency of what we produce
  • You'll help, support and mentor other members of the team and our stakeholder group with data knowledge and skills
  • You'll support other team members by delivering code reviews and data validation checks to make sure we keep our standards

About you:

  • Previous experience in an analytics engineering role
  • Strong SQL skills and experience with data warehouses (e.g., Redshift, Snowflake, BigQuery)
  • Proficiency with dbt or similar data transformation tools
  • Knowledge of data governance and best practices for data security
  • Clear and concise communication skills to explain complex technical concepts to non-technical stakeholders
  • Analytical mindset with attention to detail and curiosity to find the edge cases in data that might impact its use
  • Excellent problem-solving skills
  • Embraces new technologies and stays updated with the latest trends and tools in data analytics & engineering & AI

Added bonus:

  • Experience with Python or Airflow
  • Experience in CI/CD pipelines for data engineering workflows
#LI-JH1

At Zopa we value flexible ways of working.

We value face-to-face collaboration and a good work-life balance. This hybrid role requires you to come to our London office 2-3 days a week.

You'll also have the option of working from abroad for up to 120 days a year!* But no matter where you are, we’ll make sure you’ve got everything you need to thrive, both in your work and home life, from day one.

*Subject to having the right to work in the country of choice

Diversity Statement

Zopa is proud to offer a workplace free from discrimination. Diversity of experience, perspectives, and backgrounds leads to better products for our customers and a unique company culture for our people. We are made up of nearly 50 nationalities, have a DE&I forum made up of Zopians wanting to make a difference and we are proud of our culture where everyone can bring their full self to work. Our approach to DE&I is reflected in our hiring process so please let us know if you require any reasonable adjustments.

Our approach to AI in interviews

At Zopa, AI isn't something we're testing out — it's part of how we work every day. As a proud partner of Jobs 2030, we're committed to building AI fluency across our workforce, and we expect Zopians to use AI as part of how they do their jobs.

Because of that, we want to be transparent about how we think about AI use during our hiring process.

Behavioural and competency-based interviews: please don't use AI. These conversations are designed to understand you — your experiences, your judgment, and how you've approached real situations. An AI-generated answer can't tell us that. What it can do is get in the way of us finding out whether we're the right fit for each other.

Technical interviews: it depends on the role. Some technical stages actively welcome AI use, others don't. Your Talent Partner will let you know what's expected at each stage. Where AI is part of the assessment, we'll be interested not just in the outcome, but in how you used it – the tools you chose, your reasoning, and the decisions you made along the way.

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