Project Description:
The project involves the development and maintenance of applications used by the sales and sales support teams at InAllMedia. These applications handle lead generation, information surfacing, and allow sales representatives to manage leads and report on their activities. Additionally, the system integrates with Salesforce (SFDC) to streamline sales processes and improve efficiency.
The development team will be responsible for:
- Supporting JavaScript and Python applications.
- Managing business intake and handling ticket requests related to these applications.
- Future responsibilities may expand to include data analysis, error detection and resolution, system maintenance, performance improvements, and swift responses to downtime incidents.
- Transitioning existing applications to incorporate AI integrations.
The applications primarily rely on React.js for the front-end and Python for the back-end. Additionally, the system communicates with Salesforce via APIs, and understanding how to handle these integrations is essential.
Stack to be Used (in Order of Priorities):
- React.js + JavaScript (Front-end)
- React.js will be the primary technology for building dynamic, high-performance user interfaces (UIs).
- JavaScript will be the language used for React components and handling client-side logic, enabling seamless interaction between the front-end and back-end.
Reason: Since the application heavily involves lead management and sales activities, the front-end with React is critical to ensuring a responsive and user-friendly interface for sales representatives.
- TypeScript (Optional but Recommended)
- TypeScript will provide static typing, enhancing the maintainability and scalability of the React codebase, especially as the application grows and evolves.
- Python + Django/Flask (Back-end)
- Python will handle server-side logic and data processing, while Django or Flask will be used to structure the back-end services.
- Django is recommended for a more structured and feature-complete framework, while Flask is suitable for lightweight, custom-built applications.
- API Integrations (Salesforce)
- The system will require seamless integration with Salesforce (SFDC) via APIs to sync sales data, lead information, and performance metrics.
- Knowledge of RESTful APIs and potentially SOAP APIs for Salesforce is required.
- Data Analysis & Performance Optimization
- The team will need to implement tools and methods for data analysis, using Python libraries like Pandas or NumPy to process sales data, identify trends, and provide actionable insights.
- Performance optimization will involve identifying bottlenecks and ensuring the system scales as the number of users and data grows.
- Maintenance & Error Resolution
- The system will require ongoing maintenance and quick error resolution. This includes setting up monitoring tools like Sentry or New Relic for real-time issue tracking, and employing best practices for testing and bug fixing.
- AI Integration (Future)
- In the future, the project will involve the integration of AI functionalities to improve automation, lead qualification, and other sales processes. This could involve using frameworks like TensorFlow or PyTorch for building AI models.
Summary of Technologies in Order of Use:
- React.js + JavaScript
- TypeScript (if applicable)
- Python + Django/Flask
- API Integrations (Salesforce)
- Data Analysis & Performance Optimization
- Maintenance & Error Resolution
- AI Integration (future)