Lead Data Engineer

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August 16

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Zego

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Insurance • Transport

Zego is a company that provides flexible motor insurance solutions for various types of drivers and riders, including private hire taxi drivers, delivery drivers, and courier users. Zego's insurance products cover vehicles such as cars, scooters, motorbikes, and vans, and are designed to accommodate both personal and business use. Using technology such as the Sense telematics app, Zego offers personalized and potentially cheaper insurance premiums for safe drivers. The company collaborates with major delivery and ride-sharing platforms like Uber, Deliveroo, Just Eat, and Amazon Flex to offer tailored insurance options for their drivers. Zego emphasizes customer satisfaction, providing easy-to-use services via their app, and is a trusted provider for thousands of UK and European drivers.

201 - 500 employees

Founded 2016

🚗 Transport

💰 $150M Series C on 2021-03

📋 Description

• Lead Data Engineer to be a technical authority within our data engineering function, helping to shape and evolve our data platform • Hands-on role designing and building scalable, resilient, and secure data systems; mentor and guide other engineers • Collaborate with peers across Engineering, Data Science, Analytics, and Product to ensure our data infrastructure is efficient, reliable, and future-proof • Foster technical excellence within the team by sharing knowledge, reviewing code, and coaching others • Design, build, and maintain scalable and secure data pipelines, warehouses, and streaming systems • Ensure data is modeled 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 • 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 definition and execution of the technical roadmap for data engineering • Nice to Have: Data Mesh or Lakehouse architectures; Kubernetes, Docker, and real-time streaming (Kafka, Kinesis); ML pipelines or MLOps frameworks

🎯 Requirements

• 5+ years as a Data Engineer working on scalable data platforms • Proven expertise in designing, building, and operating ETL/ELT pipelines and large-scale data architectures • Deep hands-on experience with modern data stacks — 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) • Collaboration: Ability to work effectively with cross-functional stakeholders • Mentorship: Demonstrated experience in supporting the growth of other engineers through code reviews, pairing, and knowledge sharing • Problem-Solving: Pragmatic approach to balancing technical excellence with delivery needs • Nice to Have: Experience building Data Mesh or Lakehouse architectures; Kubernetes, Docker, and real-time streaming technologies (e.g. Kafka, Kinesis); ML pipelines or MLOps frameworks

🏖️ Benefits

• market-competitive salary • private medical insurance • company share options • generous holiday allowance • a whole lot of wellbeing benefits • annual flexible hybrid working contribution