Location
London

Hours
Full Time

Salary
Competitive salary

About the Role
At Zego, we believe traditional motor insurance holds good drivers back by being too complicated and expensive, without considering how well you actually drive. Since 2016, our mission has been to offer the lowest priced insurance for good drivers, serving van drivers, gig workers, and everyday car drivers alike. Having sold tens of millions of policies and raised over $200 million in funding, we are just getting started.

We are seeking a Senior Data Engineer to be a key technical contributor within our data engineering function, helping to build and evolve our data platform to support Zego's ambitious growth. This hands-on role involves designing and building scalable, resilient, and secure data systems while collaborating closely with Engineering, Data Science, Analytics, and Product teams to ensure efficient and reliable data infrastructure.

While this role does not include line management responsibilities, you will contribute to technical excellence by sharing knowledge, reviewing code, and supporting less experienced engineers.

Experience
4+ years as a Data Engineer working on scalable data platforms, ideally in product-led or high-growth environments.
- Proven experience designing, building, and operating ETL/ELT pipelines and large-scale data architectures.
- Hands-on experience with modern data stacks including Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark.
- Familiarity with deployment technologies such as AWS, Docker, and Terraform or similar.
- Experience supporting other engineers through code reviews, pairing, and knowledge sharing.
- Ability to work effectively with cross-functional stakeholders, translating technical concepts into business value.
- Pragmatic approach balancing technical excellence with delivery needs.
- Active curiosity about AI and its application to improve productivity and innovation.

About you
Enthusiastic and proactive with a strong sense of ownership.
Collaborative team player who enjoys sharing knowledge and supporting others.
Keen to experiment, learn quickly, and apply new tools and techniques.
Committed to maintaining high standards of technical quality and continuous improvement.

Qualifications
While formal qualifications are not specified, strong practical experience and a proven track record in data engineering are essential.

Nice to have
- Experience building Data Mesh or Lakehouse architectures.
- Familiarity with Kubernetes, Docker, and real-time streaming technologies such as Kafka or Kinesis.
- Exposure to ML engineering pipelines or MLOps frameworks.