Senior Data Engineer

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 Senior Data Engineer to be a key technical contributor within our data engineering function, helping to build and evolve our data platform to meet Zego's ambitious growth.

This is a hands-on technical role, you'll design and build scalable, resilient, and secure data systems, while supporting the wider team through knowledge sharing and collaboration. You'll work closely with peers across Engineering, Data Science, Analytics, and Product to ensure our data infrastructure is efficient and reliable.

While this role doesn't involve line management, you'll be expected to contribute to technical excellence within the team by sharing knowledge, reviewing code, and supporting less experienced engineers.

Requirements

What you will be doing

Technical Delivery & Collaboration

Act as a strong technical contributor within the Data Engineering team.

Support and help less experienced engineers grow through pairing, code review, and knowledge sharing.

Promote best practices in data engineering, including testing, CI/CD, observability, and infrastructure as code.

Platform & Architecture

Design, build, and maintain scalable and secure data pipelines, warehouses, and streaming systems.

Ensure data is modelled and structured to meet the needs of analytics, data science, and operational use cases.

Contribute to the evolution of our data architecture, ensuring it can support both current and future business needs.

Collaboration & Delivery

Partner with teams across the business to understand requirements and translate them into robust technical solutions.

Identify opportunities for optimisation, re-architecture, or tool improvements.

Contribute to the delivery of the technical roadmap for data engineering.

What you will need to be successful

Experience: 4+ years as a Data Engineer working on scalable data platforms, ideally in product-led or high-growth environments.

Solid experience designing, building, and operating ETL/ELT pipelines and large-scale data architectures.

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 similar technologies is essential).

Ability to work effectively with cross-functional stakeholders, translating technical concepts into business value.

Experience supporting other engineers through code reviews, pairing, and knowledge sharing.

Pragmatic approach to balancing technical excellence with delivery needs.

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 this uncomfortable.

Nice to have

Experience building Data Mesh or Lakehouse architectures.

Familiarity with Kubernetes, Docker, and real-t