Data Engineer

About the Job

This organisation helps both consumers and businesses make informed decisions. Working with over 6,000 brands worldwide, it collects reliable, verified customer reviews that help people understand how others feel about products and services, while enabling businesses to learn what they’re doing well and where they can improve. This creates transparent, trusted relationships and supports consistently exceptional customer experiences.

The team is made up of technology specialists, industry experts, and multi‑lingual client service professionals who operate across sectors such as travel, retail, automotive, and finance. Their AI solutions, business insights, review software, and compliance tools help clients increase sales and reduce customer churn. As a recognised partner of a major search engine provider, they also support improved search and paid conversion performance.

They work with a wide range of organisations, from large household names to smaller, local companies.

About the Role

The organisation’s dataset contains millions of interactions between users and brands globally. The role offers the opportunity to explore this data and develop innovative ways to collect, curate, and make it accessible for others.

As a Data Engineer, you will:

• Collaborate across engineering, product, and data teams to build impactful data products and infrastructure.
• Help own, maintain, and continuously improve the internal data engineering stack using industry‑leading technologies.
• Work in a hybrid pattern from the office location closest to you (London or Petersfield).

What You’ll Already Have

• 1–3 years of experience in data engineering, ideally on cloud infrastructure (the team uses Google Cloud).
• Advanced SQL skills, including writing performant queries and debugging.
• Understanding of data warehousing patterns and design techniques.
• Experience with cloud-based relational and non-relational databases, preferably BigQuery, Postgres, and Datastore.
• Familiarity with DBT for data transformation.
• Experience with ETL, pipeline design, and orchestration.
• Proficiency in an object-oriented programming language, ideally Python.

What Else You Could Bring

• Containerisation experience (e.g., Kubernetes).
• Experience optimising Looker workloads.
• Knowledge of event‑driven system design.
• Background in machine learning engineering.
• Management or mentoring experience.