Data Engineer – Geospatial Development | Qubryx

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📍 Location: Kochi (Remote/Hybrid options available)
🕒 Job Type: Full-Time
📈 Experience: 3+ Years (Data Engineering & Geospatial Development)

Job Overview

Are you passionate about geospatial data engineering?
We are hiring a Data Engineer – Geospatial Development to work with cutting-edge geospatial platforms like ESRI ArcGIS, QGIS, and Google Earth, while building scalable data pipelines, spatial data visualizations, and delivering actionable geospatial insights.

You’ll work with leading Python libraries including GeoPandas, Leafmap, Folium, Leaflet, and Mapbox in a cloud-first environment (Azure/AWS).

Key Responsibilities

  • Design, implement, and optimize spatial and non-spatial data pipelines.

  • Develop interactive geospatial dashboards and visualizations using Python libraries.

  • Analyze and process geospatial data with ArcGIS, QGIS, Google Earth, etc.

  • Integrate multiple data sources into geospatial models and visualization platforms.

  • Utilize Python tools such as GeoPandas, Folium, Leafmap, and Mapbox.

  • Manage large spatial datasets on Azure, AWS, or Google Cloud.

  • Support geospatial analytics and collaborate with Data Scientists and Analysts.

  • Ensure performance, scalability, and data integrity in all geospatial operations.

  • Document technical solutions and build reusable geospatial templates.

Required Skills

  • 3+ years of experience in Data Engineering and Geospatial Development.

  • Strong expertise in Python with geospatial libraries (GeoPandas, Shapely, Leafmap, etc.).

  • Hands-on experience with ESRI ArcGIS, QGIS, and Google Earth.

  • Experience building interactive web maps using Leaflet, Mapbox, or similar tools.

  • Solid knowledge of spatial databases like PostGIS or SQL Server with spatial extensions.

  • Understanding of coordinate systems, spatial analysis, and projections.

  • Experience managing cloud-based storage systems like Azure Blob, AWS S3, or Google Cloud Storage.

Preferred Qualifications

  • Experience with ETL workflows involving geospatial data.

  • Familiarity with Docker, CI/CD pipelines, and Agile methodologies.

  • Knowledge of geospatial metadata standards and data governance.

  • Bachelor’s or Master’s degree in Computer Science, GIS, Geomatics, or a related field.

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