LoopMe is an AI company solving one of advertising’s hardest problems: making brand advertising actually measurable, and making it perform. Our platform runs patented machine learning models across billions of consumer signals in real time, optimising campaigns toward outcomes like purchase intent, brand lift, and foot traffic rather than proxy metrics like clicks. The result is 2–5x better performance than industry benchmarks, at scale.
We operate a high-load programmatic infrastructure, processing millions of ad requests per second with sub-200ms response times globally. This isn’t a layer on top of someone else’s stack; it’s built from the ground up, in-house, by the team you’d be joining. Founded in 2012 and headquartered in London, we now have 400+ people across 19 cities and have sustained 40% revenue CAGR since 2018. The engineering problems here are real, the ownership is genuine, and the scale is significant.
The opportunity
You own the build and ongoing maintenance of our internal data lakehouse, giving our users the data they need to make better-informed, data-driven decisions. Today our data lives across BigQuery, Clickhouse, Postgres, and Elastic Search, and internal users rely on product reporting or ad hoc extracts in Rill, Tableau, and Looker.
What you’ll do
- Own the build and maintenance of our internal data lakehouse.
- Partner with our Product team to identify the core platform data that Finance and Business Development need.
- Analyse and organise raw data from our different sources.
- Build and maintain the data pipeline architecture that exposes data from our databases into our visualisation tools.
- Develop data systems and pipelines that keep data efficiently updated.
- Improve data quality and reliability.
- Partner with other engineers to maintain our tooling and pipelines.
What you’ll bring
Essential
- You bring 3+ years of experience in a data engineering role.
- You bring experience with database technologies including BigQuery, Clickhouse, and Postgres.
- You bring technical expertise with data models, data mining, and segmentation techniques.
- You bring experience with Airflow and/or dbt.
- You bring experience with cloud-based technologies running on GCS and/or AWS.
Nice to have
- Experience with Snowflake
- Analytical skills for working with unstructured datasets
What we offer
Hybrid working — flexible schedule · 1 month work-from-anywhere · Annual performance bonus · Multikafeteria (sport/culture card) · LoopMe Gives Back · Learning & development support