Data Engineer, Portugal at Zego in 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 €35,000 - €50,000 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 Data Engineer to join our data engineering function, helping to build and maintain the data platform that powers Zego's ambitious growth.

This is a hands-on technical role. You'll build and maintain scalable, reliable, and secure data pipelines, working within an established platform and architecture. You'll work closely with peers across Engineering, Data Science, Analytics, and Product to ensure our data infrastructure is efficient and reliable.

AI is central to how we work at Zego, and that extends to engineering. You'll be encouraged to use AI tools to move faster, automate the routine, and focus your time on the problems that matter most, while staying thoughtful about where and how they add value.

You'll learn from experienced engineers across the team, and you'll be encouraged to grow your technical skills while contributing to high-quality, well-tested work.

What you will be doing 🛠️

Technical Delivery

• Build, maintain, and improve data pipelines and related systems.
• Follow and help uphold best practices in data engineering, including testing, CI/CD, observability, and infrastructure as code.
• Take part in code reviews and team knowledge sharing.

Platform & Data

• Build and maintain data pipelines, warehouses, and streaming systems within our existing architecture.
• Ensure data is modelled and structured to meet the needs of analytics, data science, and operational use cases.
• Contribute to improvements in our data systems and tooling.

Collaboration & Delivery

• Work with teams across the business to understand requirements and turn them into reliable technical solutions.
• Help identify opportunities for optimisation and tool improvements.
• Deliver against the technical roadmap for data engineering.

What you will need to be successful 🏆

• Experience: 2+ years as a Data Engineer working on data platforms, ideally in product-led or high-growth environments.

• Technical Skills:

  • Experience building and operating ETL/ELT pipelines.
  • 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 some of these or similar technologies is expected).

• Collaboration: Ability to work effectively with teammates and stakeholders.

• Problem-Solving: Pragmatic approach to balancing quality with delivery needs.

• Growth Mindset: Eagerness to learn, take feedback, and grow your technical skills.

• 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:

• Familiarity with 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 produces great work and a healthy life around it.

We also make a point of getting everyone in the same room. Teams come together every quarter, and once a year the whole company does, properly. It's a serious investment and consistently one of the best parts of the year.

Here is what the last one looked like.

Benefits 🎁

💰 Market-competitive salary, benchmarked against your function and reviewed every year.

🏆 Annual performance bonus, linked to company performance and your contribution.

📈 Share options, a real stake in the company and a share in the future you build

🩺 Private medical insurance.

🏖️ Pension, generous holiday, and £1,000 a year to spend on getting to the office or learning something new.

💻 Cutting-edge systems and tools, so you always have what you need to drive your impact.

Ready to do the most impactful work of your career? We want to hear from you.

Zego, leading the AI evolution in insurance.

Equal opportunities 🌈

We're an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, or disability status.