· Minimum 5-8 years of experience in data engineering or related roles

· Familiar with GIS platforms: ArcGIS Server, PostGIS

·        Able to use spatial Python libraries: GeoPandas, Shapely

· Build scalable geospatial data pipelines for ingestion, transformation, storage, and quality checks from multiple government sources.

·        Implements data cataloging, metadata, lineage, and security; optimizes storage and performance for GIS analytics (e.g., PostGIS, data lakes).

·        Provides reliable data services and contracts to support downstream GIS analytics and front-end visualizations, collaborating closely with GIS and front-end teams.

·        Datamanagement: applies validation, cleansing, reprojection, metadata, and datalineage of geospatial data