JavaScript Developer with GIS Knowledge & Backend Skills (Python/Node.

Job Description

Job Summary: Were seeking a highly adaptable JavaScript Developer with GIS expertise , backend development skills (Python, Node.js, or Java), and a proven ability to quickly master new tools and technologies . The ideal candidate thrives in fast-paced environments, embraces emerging trends in geospatial tech, and can rapidly assimilate new frameworks or languages to deliver innovative solutions. Key Responsibilities: Adaptive Development: Rapidly learn and implement new GIS tools , libraries , or backend frameworks as project needs evolve. Stay updated with industry trends (e.g., WebGL for mapping, cloud-native GIS, AI/ML integrations) and propose adoption where relevant. Transition seamlessly between frontend, backend, and GIS tasks as required. Technical Execution: Develop scalable web applications using JavaScript/TypeScript and frameworks like React or Angular. Build robust backend services (Python/Node.js/Java) for geospatial data processing. Optimize spatial queries for performance. Problem-Solving & Learning: Quickly grasp complex geospatial or technical challenges and devise efficient solutions. Proactively identify knowledge gaps and seek resources (documentation, courses, mentorship) to upskill. Experiment with proofs-of-concept (PoCs) for new tools or methodologies. Required Skills & Qualifications: Technical Skills: Proficiency in JavaScript/TypeScript and modern frameworks (React, Angular). Backend development in Python (Django/Flask), Node.js (Express/NestJS), or Java (Spring Boot). Hands-on experience with GIS libraries (Openlayers,Leaflet, Mapbox, PostGIS) and spatial data formats (GeoJSON, Shapefiles). Learning Agility & Soft Skills: Demonstrated ability to learn new technologies rapidly (e.g., frameworks, cloud services, APIs). Strong analytical skills to deconstruct unfamiliar problems and identify learning pathways. Growth mindset with a track record of self-directed learning (e.g., certifications, open-source contributions). Flexibility to pivot between technologies and adapt to shifting project requirements. Nice to Have: Familiarity with AI/ML for geospatial analysis (e.g., satellite imagery processing).