Data Engineer

Our vision is to give everyone the belief they can make their move. We aim to make moving simpler, by giving everyone the best place to turn to and return to for access to the tools, expertise, trust, and belief to make it happen.

We’re home to the UK’s largest choice of properties and are the go-to destination for millions of people planning their next move, reading the latest industry news, or just browsing what’s on the market.

Location:
London office / Hybrid (2 days per week in the office)

Reporting to:
Head of Data Engineering

The Role

Millions of people visit the Rightmove website every month. We have a huge amount of data about how people use the site, and what this means to our customers.

You’ll be joining our growing Data Engineer & Infrastructure team – a collaborative, high‑performing group of engineers that uses this data to build the infrastructure that powers the UK’s favourite property site.

This is a hands‑on engineering role, where you will implement and maintain the technical foundations on a modern GCP‑based data platform: from writing robust Python and SQL, to deploying infrastructure with Terraform, and ensuring our pipelines are reliable, secure, and efficient.

You take pride on executing the delivery of data engineering to the highest standards: building and maintaining batch and streaming data pipelines, managing ingestion and egress processes, supporting the analytics data layer that drives and powers all our reporting and insights to power our Products across the entire business.

This is an opportunity to join an inclusive, tight‑knit, high‑calibre engineering culture. Deepen your technical experience with a modern GCP stack, and apply your data engineering expertise to a platform used by millions every day.

What You’ll Be Doing

• Build and manage data pipelines that ingest, transform, and serve data across the business
• Contribute to the design and implementation of cloud‑based infrastructure using Terraform
• Work on complex data challenges, balancing short‑term delivery with long‑term platform evolution
• Collaborate with data product owners and stakeholders to collect and refine data requirements
• Optimise data storage, infrastructure performance, and cost within our data platform
• Support the analytics data layer by enabling clean, reliable data for downstream use in Looker and Big Query
• Collaborate with analytics engineers, analysts, and data scientists to support their data use cases
• Contribute to the evolution of our self‑serve data platform and the implementation of our data strategy
• Participate in agile ceremonies, including sprint planning, refinement, and retrospectives
• Promote and practice excellent data and cloud engineering best practices, including testing, documentation, and observability

We’re looking for someone who:

• Has 3–5 years of proven experience in data engineering, working on production‑grade data pipelines and infrastructure within a large‑scale, cloud‑based data platform
• Has worked in a complex organisation with a mature or evolving data platform (e.g., Big Query, Looker)
• Has strong Python coding skills and is confident writing complex SQL queries
• Has demonstrable experience, using Terraform to successfully manage infrastructure as code in a large scale platform
• Has hands‑on experience with GCP (Big Query, GCS, Dataflow, Cloud Composer) or AWS (Redshift, S3, AWS Glue)
• Experience with dbt and understands data modelling principles and best practices
• Deep understanding of data storage, modelling, and orchestration concepts
• Has demonstrable experience setting up and managing data pipelines end‑to‑end
• Brings a collaborative and curious mindset, and enjoys working in cross‑functional teams
• Optimistic, curious and gets excited by tech, enjoys keeping up with current trends. Actively gets involved and enjoys contributing to tech events
• Is proactive, communicative, and comfortable contributing to technical discussions and design decisions
• Experience working with version control (Git) and CI/CD practices
• Awareness of data quality, privacy, and security best practices
• Knowledge of GDPR and data security best practices, as well as frameworks for testing, monitoring, and alerting in…