Staff Data Engineer
The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that he…
About Zego
Insurance hasn’t changed much in over a century. The way we live, work and travel has.
Good drivers are the entire point of Zego. Seven in 10 drivers on the road are consistently good, but until telematics came along there was no way to prove it, so nearly everyone paid a price based on averages. Zego is the company built to change that.
At Zego, we’re leading the AI evolution in insurance.
We move fast, without the layers that usually slow things down. AI takes the routine work off every team, from Finance to Product to Marketing, so people ship real code and launch custom dashboards in minutes. Engineering commits are entirely AI-assisted, which shifts the focus from team size to the quality of your thinking, and our data warehouse connects directly to an AI assistant for instant answers. Backed by a modern tech stack (Claude Code, Snowflake, Figma and Zapier) and a commitment to adopting new tools in days rather than quarters, you get complete ownership to do the most impactful work of your career.
Purpose of the role
We're looking for a Data Engineer to join our data engineering function, helping to build and maintain the data platform that powers Zego's ambitious growth.
This is a hands-on technical role. You'll build and maintain scalable, reliable, and secure data pipelines, working within an established platform and architecture. You'll work closely with peers across Engineering, Data Science, Analytics, and Product to ensure our data infrastructure is efficient and reliable.
AI is central to how we work at Zego, and that extends to engineering. You'll be encouraged to use AI tools to move faster, automate the routine, and focus your time on the problems that matter most, while staying thoughtful about where and how they add value.
You'll learn from experienced engineers across the team, and you'll be encouraged to grow your technical skills while contributing to high-quality, well-tested work.
Requirements
What you will be doing
Technical Delivery
Build, maintain, and improve data pipelines and related systems.
Follow and help uphold best practices in data engineering, including testing, CI/CD, observability, and infrastructure as code.
Take part in code reviews and team knowledge sharing.
Platform & Data
Build and maintain data pipelines, warehouses, and streaming systems within our existing architecture.
Ensure data is modelled and structured to meet the needs of analytics, data science, and operational use cases.
Contribute to improvements in our data systems and tooling.
Collaboration & Delivery
Work with teams across the business to understand requirements and turn them into reliable technical solutions.
Help identify opportunities for optimisation and tool improvements.
Deliver against the technical roadmap for data engineering.
About You
You’re a hands-on engineer who enjoys solving problems and building reliable systems. You bring solid technical fundamentals, a pragmatic mindset, and a collaborative approach to everything you do.
Experience: 2+ years as a Data Engineer working on data platforms, ideally in product-led or high-growth environments.
Experience building and operating ETL/ELT pipelines.
Hands-on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with some of these or similar technologies is expected).
Collaboration: Ability to work effectively with teammates and stakeholders.
Problem-Solving: Pragmatic approach to balancing quality with delivery needs.
Growth Mindset: Eagerness to learn, take feedback, and grow your technical skills.
You work AI-first. You will use AI daily here, and we mean daily. You do not need to arrive an expert, but you do need to arrive curious, experiment fast, and take ownership of getting good quickly. People who wait to be trained will find th
Neutral 2–4 sentence summary of what working at this company is like, drawn from public reviews and press coverage. Tone, collaboration style, pace, benefits highlights.
£45,000 – £60,000 (Glassdoor, Levels.fyi, 2025)
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