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# Senior Data Engineer

- **Company:** Zego
- **Location:** London, United Kingdom
- **Experience:** Expert
- **Salary:** £69,707
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Apache HTTP Server, Big Data, Code Review, Continuous Integration, Data Architecture, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Security, Python (Programming Language), Machine Learning, Data Mesh, SQL Databases, Data Streaming, Snowflake, Apache Spark, Build Management, Kubernetes, Apache Kafka, Data Management, Machine Learning Operations, Terraform, Stream Processing, Data Pipelines, Docker
- **Published:** November 11, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5961468638

## About the Role

* 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-time streaming technologies (e.g. Kafka, Kinesis).
 * Exposure to ML engineering pipelines or MLOps frameworks.

Teams work better with time to collaborate and space to get things done. We call it Zego Hybrid: some of us are in our office (central London, Gibraltar or Halifax) weekly, others monthly or quarterly. It's about finding the balance between face time and focus that produces great work and a healthy life around it.

## Description

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.

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.