GIS Data Engineer
Core
Extract and transform geospatial layers into tabular data to integrate with other data sources for building credit risk/ESG scoring variables.
Role type
GIS Data Engineer
Builds
Tabular datasets for risk scoring pipelines
Domain
Banking / Geospatial Data Engineering
Deliverable
production ML models | product features
Required skills
Geospatial data extraction, spatial joins, attribute extraction from geometries, buffer operations, intersection analysis, tabular export (CSV/Parquet/SQL), spatial databases (PostGIS/BigQuery GIS/Snowflake), advanced SQL
Preferred skills
Financial sector experience, climate/ESG risk data sources, Python (geopandas/shapely), stakeholder communication
Technologies
CARTO, ArcGIS/Esri, QGIS, PostGIS, BigQuery GIS, Snowflake, Python, geopandas, shapely
Responsibilities
Extract geometries and convert to tabular attributes, execute spatial joins between risk layers and client locations, define and document spatial cross-referencing methodology, produce clean structured datasets, validate data quality and consistency, document processes for reproducibility
Seniority
Mid-level (3-5 years experience)