Description
Zoopla is one of the UK's most instantly recognisable property brands, known and loved by over 91% of the nation. 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.
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.
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.
Responsibilities:
- Setting the direction for Data Engineering and communicating 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.
- 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.
Requirements:
- 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.
Benefits:
- Hybrid working setup, with 3 days in the office per week
- 25 days annual leave + additional leave benefits
- Cycle to work and electric car schemes
- Free Calm App membership
- Enhanced Parental leave
- Fertility Treatment Financial Support
- Group Income Protection and private medical insurance
- Gym on-site in London
- 7.5% pension contribution by the company
- Discretionary annual bonus up to 10% of base salary