Geospatial Specialist (Geospatial Data Scientist)

Telekom HBS, part of the Telekom Group, is an ICT Systems Integrator offering a comprehensive suite of ICT Solutions and Services. Telekom HBS specializes in Cloud, Data Centre operations, Networking, Cybersecurity, BI and Data Warehouse, Big Data, Service Desk, Proactive Monitoring, Operations and Support, Service Management, Project and Programme Management, and Professional Services.

• Advanced university degree in Geographic Information Systems, Geography, Geomatics, Geospatial Science, Environmental Science, Computer Science, Data Science, Engineering, or related fields; first-level degree with relevant experience may be accepted.
• Proven professional experience in GIS, geospatial data engineering, spatial analytics, or geospatial solution implementation.
• Hands-on experience with raster and vector datasets, administrative boundaries, sub-national data, coordinate reference systems, spatial metadata, and geospatial data quality controls.
• Experience in 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.
• Experience with GIS formats and standards including GeoJSON, Shapefile, KML/KMZ, CSV with coordinates, GeoTIFF, and web mapping or geospatial service patterns such as WMS, WFS, WCS, OGC API Features, and OGC API Tiles.
• Proficiency with GIS desktop, server, and/or open-source geospatial tools such as ArcGIS, QGIS, GDAL/OGR, GeoPandas, PostGIS, GeoServer, MapServer.
• Skilled in Python for geospatial processing using libraries like GeoPandas, Rasterio, Shapely, Fiona, PyProj, Xarray.
• Experience with SQL and spatial SQL, especially with PostGIS, SQL Server spatial, or equivalent spatial databases.
• Cloud-based geospatial processing experience in Azure, AWS, or Google Cloud.
• Experience with data lake or lakehouse architectures and geospatial data integration in analytics platforms.
• Familiarity with metadata standards such as ISO 19115, DCAT/DCAT-AP, Dublin Core.
• Advantageous knowledge of SDMX, environmental indicators, statistical/geospatial integration, or international reporting frameworks.
• Strong problem-solving skills and ability to assess feasibility, complexity, risks, dependencies.
• Clear communication of geospatial concepts to technical and non-technical audiences.
• Attention to data quality, reproducibility, documentation, and maintainability.
• Ability to collaborate with multidisciplinary teams and manage independent work.
• Awareness of data governance, responsible data management, interoperability, and open data principles.
• Excellent command of written and spoken English.

Nice to have:

• Azure Data Engineering related certifications
• Azure Data Scientist Associate

• Review project requirements, client documentation, source datasets, reference geographies, and existing geospatial platform capabilities to define the geospatial implementation baseline.
• Assess geospatial data readiness, including raster datasets, vector layers, administrative boundaries, sub-national datasets, coordinate systems, spatial metadata, and known data quality constraints.
• Design and implement geospatial data preparation workflows, including geometry validation, coordinate reference system handling, reprojection, format normalization, clipping, joining, aggregation, simplification, enrichment, and spatial quality checks.
• Support raster and vector data processing requirements, including raster preparation, vector layer management, spatial indexing, tiling considerations, and preparation of datasets for downstream analytics, APIs, map services, or visualization layers.
• Participate in technical discussions with client stakeholders to clarify geospatial requirements, confirm assumptions, assess feasibility, explain limitations, and support acceptance of delivered outputs.
• Support the analysis, design, implementation, validation, and documentation of geospatial capabilities for the current project and future related initiatives.
• Implement or configure agreed geoprocessing functions, including buffering, proximity analysis, spatial aggregation, pattern analysis, classification, composite indexing, clipping, spatial joins, and sub-national processing.
• Support the preparation and publication of geospatial outputs via GeoJSON, Shapefile, CSV with coordinates, GeoTIFF, map services, OGC aligned service patterns, APIs, or export packages.
• Provide technical input to API and interoperability teams on geospatial service requirements, including OGC WMS, WFS, WCS, OGC API patterns, GeoJSON, metadata alignment, and geospatial API payload structures.
• Collaborate with data engineering and data architecture teams to ensure proper integration of geospatial datasets into ingestion, transformation, validation, metadata, governance, and publication workflows.
• Support geospatial metadata, provenance, quality, and lineage requirements with data governance and catalogue teams.
• Define and execute geospatial validation activities such as sample maps, spatial accuracy checks, comparison against reference layers, export validation, format validation, and document known limitations.
• Advise on geospatial performance considerations, including map loading, spatial query patterns, export size, raster processing complexity, tile generation, and service consumption patterns.
• Prepare technical documentation, configuration notes, supported format descriptions, workflow diagrams, validation evidence, operational considerations, and handover materials for technical teams.