GIS DATA ENGINEER

Knowledge of GIS, data modelling, and data engineering are key to this position.

Domain expertise for geospatial data validation, enrichment, and optimization.

This role ensures that geospatial data is validated, standardized, and enriched with contextual attributes such as zoning and roads to meet business ready requirements.

Required Technical Skills

Bachelor’s degree in GIS, Computer Science, Data Science, or a related field

8+ years of experience in geospatial engineering and GIS systems.

Expertise in Apache Sedona (GeoSpark) for distributed geospatial joins and partitioning.

Proficiency in PostGIS with advanced spatial SQL (ST_Intersects, ST_DWithin, ST_Buffer, ST_Union).

Experience in handling multiple geometry formats and CRS validation.

Familiarity with Spark/EMR integration for scalable geospatial processing

Knowledge of GIS software (e.g., ArcGIS, QGIS) and geospatial data formats (e.g., shapefile, GeoJSON, KML)

Experience with Python, AWS Cloud, ETL processes and tools

Strong skills in spatial indexing and query optimization on large datasets.

Excellent problem-solving and analytical skills

Responsibilities

Design and implement geospatial data models

Develop and optimize data ETL processes

Validate incoming geospatial datasets for geometry correctness and CRS compliance (EPSG:4326).

Implement distributed spatial joins using Apache Sedona/GeoSpark to enrich parcels with supporting layers (roads, zoning, boundaries).

Standardize geometry handling across multiple dataset types (points, polygons).

Work with Cloud Data Engineers to ensure schema mapping and cleansing aligns with standards.

Optimize queries and enrichment processes for Aurora PostGIS using spatial indexes (GIST, BRIN).