About the Role
An exciting opportunity for an experienced Geospatial Data Engineer to join an innovative, fully funded, start-up technology business developing automated solutions within the transport and mobility sector.
Responsibilities
•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.
Requirements
•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.
•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.
•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.
Nice to Have
•Experience in transport, mapping, surveying, logistics or mobility technology.
•Knowledge of parking regulations, road-user charging, GNSS positioning, map matching or spatial machine learning.
Conditions
No conditions stated in the posting.
