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Open nowPosted 11 hours ago

Geospatial Specialist (Geospatial Data Scientist)

Workable (global search)107,801 open roles

Where
Belgium
Work mode
Remote
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Your applicationOpen nowGeospatial Specialist (Geospatial Data Scientist)Workable (global search) · Belgium

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  5. 34.0%30 days
This job: posted 11 hours ago

Workable (global search) median: 2 days open

The posting

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 delivering ICT Services in areas such as 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. We are seeking a Geospatial Data Scientist to join our team and be responsible for the following tasks:

  • 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, which may include 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 through agreed mechanisms, such as GeoJSON, Shapefile, CSV with coordinates, GeoTIFF where applicable, 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 where applicable.
  • Work with data engineering and data architecture teams to ensure geospatial datasets are correctly integrated into ingestion, transformation, validation, metadata, governance, and publication workflows.
  • Support geospatial metadata, provenance, quality, and lineage requirements in coordination with data governance and catalogue teams.
  • Define and execute geospatial validation activities, including sample maps, spatial accuracy checks, comparison against reference layers, export validation, format validation, and documentation of 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 clear technical documentation, configuration notes, supported format descriptions, workflow diagrams, validation evidence, operational considerations, and handover materials for technical teams.

Requirements

  • Education: Advanced university degree in Geographic Information Systems, 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.
  • Professional Experience: Proven professional experience in GIS, geospatial data engineering, spatial analytics, or geospatial solution implementation.
  • Geospatial Data Experience: Hands-on experience with raster and vector datasets, administrative boundaries, sub-national data, coordinate reference systems, spatial metadata, and geospatial data quality controls.
  • Implementation Experience: 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.
  • Standards and Interoperability: Experience with common 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.

Required Technical Skills:

  • GIS desktop, server, and/or open-source geospatial tools such as ArcGIS, QGIS, GDAL/OGR, GeoPandas, PostGIS, GeoServer, MapServer, or equivalent technologies.
  • Python for geospatial processing, including libraries such as GeoPandas, Rasterio, Shapely, Fiona, PyProj, Xarray, or similar.
  • SQL and spatial SQL, especially with PostGIS, SQL Server spatial, or equivalent spatial database capabilities.
  • Cloud-based geospatial processing experience, particularly in Azure, AWS, or Google Cloud environments.
  • Experience with data lake or lakehouse architectures and geospatial data integration in analytics platforms.
  • Familiarity with metadata standards relevant to geospatial and open data, such as ISO 19115, DCAT/DCAT-AP, Dublin Core, or equivalent.
  • Understanding of SDMX, environmental indicators, statistical/geospatial integration, or international reporting frameworks is an advantage.

Required Soft Skills / Competencies:

  • Strong problem-solving skills and ability to assess technical feasibility, complexity, risks, and dependencies.
  • Ability to communicate geospatial concepts clearly to technical and non-technical stakeholders.
  • Strong attention to data quality, reproducibility, documentation, and operational maintainability.
  • Ability to work collaboratively with data engineers, data architects, API developers, governance specialists, project managers, and client stakeholders.
  • Ability to work independently, manage priorities, and deliver outputs within agreed timelines.
  • Awareness of data governance, responsible data management, interoperability, and open data principles.
  • Excellent command of written and spoken English.

Desirable certifications:

  • Azure Data Engineering related certifications
  • Azure Data Scientist Associate
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