About the Role
We are looking for a dependable, hands-on GIS Analyst to deliver accurate, production-ready geospatial datasets. The role is primarily focused on manual GIS compilation work which includes data capture, digitization, editing, cleaning, quality checks, and delivery, carried out per user and project requirements. You will own day-to-day GIS production tasks end to end and progressively contribute to workflow improvement and semi-automation using Python, AI assistants, and geospatial tools, as the team evolves toward cloud computing and cloud-native geospatial workflows.
Perform GIS production work — digitization, feature capture, editing, attribution, georeferencing, projection management, clipping, mosaicking, format conversion, and map preparation — using industry-standard GIS desktop tools.
Create, clean, and maintain vector and raster datasets; run geometry repair, topology, duplicate, gap/overlap, attribute, and completeness checks before every delivery.
Interpret satellite and aerial imagery, basemaps, and reference layers to capture or validate buildings, land use, infrastructure, terrain, and other exposure-related features.
Process to DEM, DSM, DTM, LiDAR, contours, and elevation-derived data for terrain and building-height analysis under project guidance.
Manage large datasets in common formats: File Geodatabase, GeoPackage, Shapefile, GeoTIFF, CSV, KML/KMZ, and GeoJSON.
Follow SOPs, naming conventions, folder structures, metadata standards, and QC checklists; maintain traceability of source data and edits.
Support semi-automation of repetitive steps using ModelBuilder, QGIS Processing Modeler, Python, ArcPy, GDAL, or related libraries.
Leverage AI assistants such as Claude, where appropriate, to assist with coding, debugging, and developing GIS solutions, while reviewing and validating all AI-assisted output before use.
Document methods, assumptions, data limitations, validation results, and reusable workflows clearly and professionally.
Bachelor’s or Master’s degree in GIS, Geoinformatics, Geography, Remote Sensing, Geomatics, Civil/Environmental Engineering, or a related discipline.
3–5 years of hands-on GIS or remote-sensing experience; strong practical capability may also be considered.
Proficiency in ArcGIS Pro, QGIS, or equivalent tools for spatial analysis, digitization, cartography, and quality control.
Strong understanding of coordinate systems, raster/vector data, geoprocessing, geodatabases, topology validation, and data cleaning.
Working knowledge of remote-sensing imagery, elevation data, and LiDAR products, with the ability to manage large geospatial datasets accurately.
Basic-to-intermediate Python for GIS, familiarity with ArcPy or open-source geospatial libraries, and basic SQL skills.
Ability to troubleshoot and modify existing scripts and automate repetitive GIS workflows.
Familiarity with AI-assisted scripting and prompt engineering, including validation of AI-generated code and results.