Geospatial Data Engineer

This is a hands-on role where you’ll play a key part in building accurate, reliable transport datasets and developing the data pipelines and spatial models that underpin software solutions. Working closely with the development team, you’ll help transform complex and fragmented data into high-quality, structured information to support location recognition, geofencing and the automation of transport-related processes., * Build and maintain data pipelines to ingest, clean, standardise and update transport data from APIs, GIS files, spreadsheets and other sources.

• Design and develop spatial data models using PostgreSQL/PostGIS, covering parking bays, traffic restrictions, tolls and congestion-charge zones.
• Develop and refine geofencing and location-recognition models, working closely with developers to address positioning uncertainty and complex boundary cases.
• Analyse and improve geospatial data quality, resolving issues involving geometries, coordinate systems, topology, missing data and inconsistencies.
• Apply AI-assisted extraction and classification techniques to process complex documents and datasets, ensuring outputs are validated and traceable.
• Develop automated quality checks to measure positional accuracy, completeness, consistency and data freshness.
• Build reusable tools and integrations to make transport datasets accessible and easy to use within software applications.
• Conduct targeted site surveys and GNSS observations where required to verify mapped features and improve accuracy.
• Maintain version-controlled code, automated testing, reproducible workflows and clear technical documentation.
• Help establish a scalable technical foundation to expand data coverage across London and beyond.

You’ll be an experienced Geospatial Data Engineer, GIS Engineer or similar, with a strong technical background in processing location-based data and turning complex information into reliable, usable datasets.

You’ll ideally have experience with:

• Python and SQL, including building data pipelines and API integrations.
• PostgreSQL/PostGIS and spatial data modelling.
• GIS tools such as QGIS and geospatial libraries including GeoPandas, Shapely or GDAL.
• Geospatial concepts including coordinate systems, spatial accuracy, topology, spatial joins and geofencing.
• Processing formats such as GeoJSON, GeoPackage, shapefiles, CSV and JSON.
• Applying AI to data extraction, processing or quality assurance.
• Software engineering best practices, including Git, testing, reproducible workflows and technical documentation.

You’ll also be an analytical problem-solver who enjoys investigating complex data issues, improving data quality and working collaboratively with developers to deliver practical solutions.

A willingness to undertake occasional field verification across London is important when mapping issues cannot be resolved through desk-based analysis alone.

Experience in transport, mapping, surveying, logistics or mobility technology would be useful, as would knowledge of parking regulations, road-user charging, GNSS positioning, map matching or spatial machine learning., You’ll be able to make a tangible contribution to the development of its data capabilities, working on real-world challenges at the intersection of geospatial engineering, data quality, automation and AI.