zopa - Senior Analytics Engineer
Requirements
• Thrives in a developing environment where not everything is defined • Communicates clearly with engineers, product teams and business stakeholders • Can influence without authority • Has strong problem-solving and critical thinking skills • Is comfortable making decisions in ambiguity • Enjoys mentoring and raising standards • Is proactive about identifying and solving structural problems • Embraces continuous learning and technological advancement • Significant experience as a Senior or Lead Analytics Engineer • Demonstrable experience setting technical standards or shaping modelling practices • Strong expertise in SQL and building production-grade, cost-efficient dbt models • Experience working in modern cloud data environments • Strong understanding of data governance and risk considerations • Experience working cross-functionally in product-led environments • Solid understanding of CI/CD, Git-based workflows, and version-controlled deployments • 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.
Responsibilities
• Evolve the technical direction for Analytics Engineering in partnership with the Head of AE • Develop scalable modelling patterns aligned to our data mesh and domain-based ownership approach • Raise engineering standards across testing, CI/CD, documentation, version control and code review • Lead by example in applying data governance and risk standards across all data products • Design and build robust, production-grade, cost-efficient dbt models for high-impact domains • Own modelling strategy for key business areas, ensuring consistency, maintainability, and scalability • Optimise data marts for performance, reliability and long-term growth • Break down complex domain problems into scalable data products • Evaluate trade-offs between cost, performance, maintainability and delivery speed • Take end-to-end ownership of high-impact modelling initiatives • Partner with product teams and domain owners to translate business needs into clean, well-documented data models • Ensure cross-domain consistency and reusability of shared entities • Advocate for domain ownership and clear data contracts • Simplify overly complex modelling areas and reduce unnecessary warehouse costs • Mentor Analytics Engineers and Analysts, helping them deepen their modelling and engineering expertise • Provide high-quality, empathetic and actionable code reviews • Share knowledge at scale through documentation, technical sessions or playbooks
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