We are seeking a highly skilled Data Engineer with experience in geospatial data processing and visualization.
The ideal candidate will have strong Python skills along with experience in geospatial platforms like ESRI
ArcGIS, QGIS, and Google Earth. You should be comfortable developing map-based interfaces and
visualizations using libraries such as GeoPandas, Leafmap, Leaflet, Mapbox, and Folium. This role will also
involve developing robust data pipelines, managing spatial data storage, and supporting analytics and insights on
geospatial datasets.
Key Responsibilities:
• Design, implement, and optimize spatial and non-spatial data pipelines.
• Develop interactive geospatial data visualizations and dashboards using modern Python libraries and
mapping tools.
• Work with tools like ESRI ArcGIS, QGIS, and Google Earth to process and analyze geospatial data.
• Integrate various data sources into geospatial data models and visualization platforms.
• Leverage Python (GeoPandas, Folium, Leaflet, Mapbox, Leafmap, etc.) for geospatial data
transformation and analysis.
• Manage large spatial datasets in cloud environments (preferably Azure or AWS).
• Collaborate with data scientists and analysts to deliver geospatial insights.
• Ensure data integrity, performance, and security in all pipeline operations.
• Document technical solutions and develop reusable components and templates.
Required Skills:
• 3+ years of experience in Data Engineering and geospatial development.
• Proficiency in Python with geospatial libraries (GeoPandas, Shapely, Leafmap, Folium, etc.).
• Hands-on experience with ESRI ArcGIS, QGIS, Google Earth, or similar platforms.
• Experience with web mapping tools and interfaces (Leaflet, Mapbox).
• Strong skills in SQL and working with spatial databases (PostGIS, SQL Server with spatial extensions).
• Solid understanding of coordinate systems, projections, and spatial analysis techniques.
• Cloud experience with services such as Azure Blob Storage, Azure Data Factory, AWS S3, or Google
Cloud Storage.
Preferred Qualifications:
• Familiarity with ETL workflows involving spatial data.
• Experience with containerization tools (Docker) and CI/CD pipelines.
• Exposure to Agile methodologies and collaborative team environments.
• Knowledge of metadata standards and geospatial data governance practices.
• Bachelor’s or Master’s in Computer Science, GIS, Geomatics, or a related field.
Python, GeoPandas, Folium, Leaflet, Mapbox, Leafmap, ArcGIS, QGIS, Google Earth, SQL, PostGIS, Spatial Databases, AWS, Azure, ETL Pipelines, Geospatial Analytics, Docker, CI/CD, GIS, Spatial Analysis