Geospatial Specialist (Geospatial Data Scientist)
New
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Telekom HBSGeospatial data
Workable workplace: remote; Workable locations: Greece. Romania. Poland. Germany. Belgium. FranceContract
Salary not disclosed
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Job Details
- Languages
- Excellent command of written and spoken English.
- Required Skills
- PythonSQL
Requirements
- Hold an advanced university degree in GIS, Geography, Geomatics, Geospatial Science, Environmental Science, Computer Science, Data Science, Engineering, or a related field; a first-level university degree with additional relevant experience may be accepted.
- Have professional experience in GIS, geospatial data engineering, spatial analytics, or geospatial solution implementation.
- Have hands-on experience with raster and vector datasets, administrative boundaries, sub-national data, coordinate reference systems, spatial metadata, and geospatial data quality controls.
- Have experience designing and implementing geospatial workflows, such as data preparation, reprojection, geometry validation, spatial joins, aggregation, clipping, proximity analysis, buffering, raster processing, or map layer publication.
- Have experience with GIS formats and standards including GeoJSON, Shapefile, KML/KMZ, CSV with coordinates, GeoTIFF, WMS, WFS, WCS, OGC API Features, or OGC API Tiles.
- Have experience with GIS desktop, server, or open-source tools such as ArcGIS, QGIS, GDAL/OGR, GeoPandas, PostGIS, GeoServer, or MapServer.
- Use Python for geospatial processing, including libraries such as GeoPandas, Rasterio, Shapely, Fiona, PyProj, or Xarray.
- Have SQL and spatial SQL skills, particularly with PostGIS, SQL Server spatial, or equivalent spatial database capabilities.
- Have cloud-based geospatial processing experience, particularly in Azure, AWS, or Google Cloud.
- Have experience with data lake or lakehouse architectures and geospatial data integration in analytics platforms.
- Be familiar with geospatial and open-data metadata standards such as ISO 19115, DCAT/DCAT-AP, or Dublin Core.
- Demonstrate problem-solving, clear stakeholder communication, attention to data quality and documentation, collaboration, independent prioritization, and awareness of data governance and open-data principles.
Responsibilities
- Review project requirements, client documentation, source datasets, reference geographies, and platform capabilities to define the geospatial implementation baseline.
- Assess geospatial data readiness, including coordinate systems, metadata, administrative boundaries, and data quality constraints.
- Design and implement data preparation workflows for validation, reprojection, normalization, clipping, joining, aggregation, enrichment, and quality checks.
- Process raster and vector data and prepare datasets for analytics, APIs, map services, and visualization layers.
- Clarify geospatial requirements with client stakeholders, assess feasibility, explain limitations, and support acceptance of delivered outputs.
- Implement or configure geoprocessing functions such as buffering, proximity analysis, spatial aggregation, classification, and spatial joins.
- Prepare and publish geospatial outputs through agreed formats, map services, OGC-aligned patterns, APIs, or export packages.
- Provide geospatial service and payload requirements to API and interoperability teams.
- Coordinate with data engineering, architecture, governance, and catalogue teams on integration, metadata, provenance, quality, and lineage.
- Execute geospatial validation, advise on performance, and prepare technical documentation and handover materials.
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