About the role
A single container can send updates from a shipping line, a port terminal, a rail operator and a customs broker, each in a different format and often out of order. Customers only want to know one thing: where is my freight, and will it arrive on time? You will build the data layer that answers that question.
What you will do
- Own ingestion from 60 carrier feeds and normalise them into a shared event model.
- Model shipment timelines in dbt and BigQuery, with tests that catch bad data before customers do.
- Work with the operations team to find where timelines go wrong, and fix the root cause.
What you will bring
- Three or more years as a data or analytics engineer, working with Python and SQL daily.
- Experience with orchestration (Airflow, Dagster or similar) and modern warehouse tooling.
- Curiosity about the physical world your data describes.
Pay and benefits
Three days a week at our office by the Maas, two from home. 27 days of leave, a travel card for public transport, and 8% holiday allowance on top of the listed salary.