At Savills, we are looking for a Data Engineer who knows what it is like to work within an organization, take responsibility for their own work, and collaborate in a team.

You don't have to be able to do everything yet. What we are looking for is the basics, the right attitude, and the will to grow.

This role is deliberately not for everyone. You won't be working with the latest AI technologies on a daily basis, and you won't end up in a large engineering team full of specialists. What you *do* get is a lot of autonomy, long-term ownership, a healthy work-life balance, and the space to develop yourself in a team where your work makes a direct difference.

Where will you end up?

You will become part of the Insight & Data team at Savills Netherlands. This team is part of the broader Data, Intelligence & Strategy (DIS) department, which supports Savills teams with market insights, custom applications, and data solutions that feed the real estate advisory and investment practice. The solutions we build support the research, market analyses, and data insights with which Savills advises its clients.

As the Insight & Data team, we are responsible for virtually all custom data solutions within the organization. This ranges from ETL processes, databases, and dashboards to web applications, geographic applications, and automated information services. As a result, you will deal with both the technology and the business that uses what we build. Our environment includes Python, PostgreSQL, Azure, GitHub, Power BI, Esri, FastAPI, and React, among others.

What are you going to do?

• Building and maintaining ETL processes in Python.
• Working with PostgreSQL databases.
• Developing new data streams and connections with external data sources.
• Improving existing processes and data sources.
• Supporting colleagues with data-related issues.
• Contribute to larger projects within the data landscape.

After your onboarding period, you will gain increasing ownership of your own data domain, including the associated data sources, ETL processes, data quality, and business knowledge.