Data Engineering Manager

Who We Are

Zoopla is one of the UK’s most instantly recognisable property brands. In fact, we’re known and loved by over 91% of the nation (and we’re working hard on the other 9%). Our mission is to help the nation make better home decisions - by connecting everyone to their home and giving them personalised insights to help with moving, managing or financing. Over 50 million people visit Zoopla every month to access exclusive data and information on every UK property, search over 500,000 homes for sale and rent, find the best agents and secure the latest mortgage deals.

We’re a growing, dynamic team that embraces innovation and isn’t afraid to push the boundaries. We’re only just starting our journey to redefine the digital property landscape, with much more to explore and achieve. Join us, and transform the way the nation makes home decisions.

About the Role

We’re looking for a Data Engineering Manager to lead us into the future.

The Data team exists to turn Zoopla’s data into value: better decisions for the business, better products for our consumers and customers, and direct revenue where the data itself is the product. Data Engineering is the foundation all of that runs on.

Databricks on AWS is our single foundation, with dbt for modelling, Fivetran for SaaS sources and AWS services for internal sources. Our ingestion and export patterns grew one at a time over several years. We want a small number of patterns that are clear, owned and easy to run, by reducing that overhead we’ll be able to focus on even more ambitious projects alongside the platform team.

You’ll report to the Director of Data and lead a team of four data engineers. You’ll work very closely with our Head of Engineering Platform and Head of Product Platform, so that our technical systems align and we can make long term choices together.

This is a player coach role, we want our leaders out in front. The balance may change depending on the direction you set and where the team goes.

What You’ll Do

• Setting the direction for Data Engineering and communicating it. We have ideas, but we want one person with the remit to own and drive it.
• Building a shared roadmap with the Head of Platform Engineering and Head of Product for Platform, so Data Engineering work is planned in from the start. Bringing a view, challenging theirs, and agreeing where data architecture and platform architecture meet.
• Putting governance in place that people and AI can follow.
• Making AI part of how the team works, and bringing Data Engineering into our software factory.
• Owning our Fivetran relationship and its cost.
• Leading, coaching and growing the team. Hiring well, giving clear feedback, and sharing knowledge so nobody is the only person who understands a piece of the platform.

How We Work

Data Engineering sits in the Data team alongside Analytics Engineering, Analytics and Data Science, and works side by side with Platform Engineering and Platform Product.

We’re AI forward, maybe it doesn’t get everything right now, but what’s to say it won’t tomorrow.

Requirements

About You (Key Attributes)

• Experience leading data engineering initiatives and setting technical direction, with formal line management experience OR a strong track record of mentoring engineers, leading projects, and a clear desire to step into people management.
• Deep experience with a modern lakehouse, ideally Databricks and Unity Catalog, and with dbt.
• Comfortable on AWS and with infrastructure as code (Terraform), and able to hold your own in a design review with platform engineers.
• Strong grounding in ingestion and integration patterns: managed connectors, change data capture, event-driven and streaming ingestion, and reverse ETL or file-based exports to external systems and customers.
• Practical data governance: access control, data contracts, data quality and personal data handling, applied so teams can move faster.
• Experience using AI tools in engineering work, with a clear view on where they help, and how to keep them safe.
• You build strong partnerships with engineering and product leaders, and you can disagree well and still land on a shared plan.
• You know what your platform costs and what the business gets back for it.

Nice to Have

• Fivetran, RudderStack or similar ingestion and reverse ETL tools.
• Experience running vendor relationships and contract renewals for data tooling.
• Exposure to Model Context Protocol (MCP) serv…