О компании
Zego builds real-time, AI-driven infrastructure for innovative insurance, providing good drivers with coverage that reflects how they actually drive.
Задачи
•Act as a strong technical contributor within the Data Engineering team
•Support less experienced engineers through pairing, code reviews, and knowledge sharing
•Promote data engineering best practices, including testing, CI/CD, observability, and infrastructure as code
•Design, build, and maintain scalable and secure data pipelines, warehouses, and streaming systems
•Ensure data is modelled and structured for analytics, data science, and operational use cases
•Contribute to the evolution of the data architecture to support current and future business needs
•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
Требования
•4+ Years of experience 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; experience with technologies similar to Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, Apache Spark, AWS, Docker, and Terraform is essential
•Ability to work effectively with cross-functional stakeholders and translate 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
•Curiosity, fast experimentation, and ownership of developing AI skills; candidates who wait to be trained may find the role uncomfortable
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
Условия
•Bonus and share options
•Private medical insurance
•Pension and generous holiday
•£1,000 a year to spend on getting to the office or learning something new
•Teams meet in person quarterly, and the whole company meets once a year
