Senior Data Engineer, Portugal

About Zego

At Zego, we're on a mission to do the good thing, not the insurance thing.

Insurance hasn't changed much in over a century. The way we live, work and travel has. We're building the real-time, AI-driven infrastructure that powers innovative insurance, so good drivers get cover that works the way they actually drive.

We're not just updating insurance; We're leading the AI evolution in insurance

For us, AI isn't a line on a roadmap or a buzzword on a slide. It's our operating reality, and it's how we build products that back drivers instead of the old insurance playbook.

We don't do things slowly, and we don't do bureaucracy. We back high-performance builders who want ownership, early responsibility and the chance to do the most career-defining work of their lives. You'll get the space to try things, the tools to move fast, and the room to see your ideas reach millions of drivers.

Do not take our word for it. Read what Zegons say about us on Glassdoor.

If you're ready to build the future of insurance, we're hiring.

Location Portugal | Compensation package €55,000 - €70,000 base + Bonus + Share Options + Benefits | Ways of working remote with quarterly visits to our London office

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.

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

Pay Transparency

At Zego, we are committed to pay transparency and equal pay practices. In compliance with EU pay transparency regulations, we proactively disclose salary information for all open positions to ensure fairness and clarity in our recruitment process. We believe transparency builds trust and helps candidates make informed decisions about their careers with us.

The Zego ways of working

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 or Halifax) weekly, others monthly or quarterly. It's about finding the balance between face time and focus that prod