2.0 - 7.0 years

8 - 17 Lacs

noida

Work from Office

Project Overview Prestigious Client / Project: Contributing to a high-impact digital transformation initiative for a leading telecom enterprise. The project is spearheaded by InnovationM and focuses on developing a location-based services platform using geospatial intelligence. Revolutionizing Technologies: Leverage advanced Python frameworks (Django/Flask), spatial databases (PostGIS/PostgreSQL), GIS data processing, RESTful APIs, Redis caching, and asynchronous programming to build scalable backend systems in the geospatial domain. Agile Development: Collaborate within a fast-paced agile environment, ensuring iterative delivery, continuous integration, and seamless cross-functional coordination to enhance performance, maintainability, and system scalability. Role and Responsibilities Develop backend services and APIs using Python (Flask) Handle GIS data processing and location-based data handling Design scalable and secure backend architecture Work with spatial and relational databases (PostGIS, PostgreSQL, MySQL) Implement ORMs like Django ORM or SQLAlchemy Perform data validation, serialization, and caching (Redis) Optimize performance, handle asynchronous programming, and ensure clean code Collaborate across teams and contribute to documentation and debugging Requirements Python Programming: Strong hands-on experience with core Python Flask Development: Backend development using any of the mentioned framework RESTful API Development: Building and integrating APIs for web services PostGIS / PostgreSQL / MySQL: Working with spatial and relational databases ORM (Django ORM / SQLAlchemy): Managing database interactions efficiently GIS Data Processing: Handling and processing geospatial datasets Data Validation & Serialization: Ensuring data quality and format consistency Backend Architecture Design: Designing scalable and maintainable services Debugging & Documentation: Identifying issues and maintaining clear technical documentation Good-to-Have Skills:- Location-Based Data Handling: Managing and querying spatial/location data Redis / Caching: Enhancing performance through caching mechanisms Asynchronous Programming: Managing concurrent backend tasks efficiently Performance Optimization: Improving system response and load handling Domain Knowledge GIS / Survey Applications: Familiarity with mapping or location-based services Collaboration & Profiling: Working in teams and using tools for code analysis

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