Job Summary
We are seeking a highly skilled Data Engineer with experience in geospatial data processing and visualization. The ideal candidate will have solid Python skills along with experience in geospatial platforms like ESRI Arc GIS, QGIS, and Google Earth. You should be comfortable developing map-based interfaces and visualizations using libraries such as Geo Pandas, 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 Arc GIS, QGIS, and Google Earth to process and analyze geospatial data. Integrate various data sources into geospatial data models and visualization platforms. Leverage Python (Geo Pandas, 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 (Geo Pandas, Shapely, Leafmap, Folium, etc.). Hands-on experience with ESRI Arc GIS, QGIS, Google Earth, or similar platforms. Experience with web mapping tools and interfaces (Leaflet, Mapbox). Strong skills in SQL and working with spatial databases (Post GIS, 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 S
📌 Data engineer (Kerala)
🏢 Qubryx
📍 Kerala