Python Developer - Django/Flask (4-6 yrs)

We are looking for an experienced Python Developer with expertise in Flask/Django frameworks to design and maintain scalable, data-driven backend applications. The ideal candidate will possess strong backend development skills, with a focus on SQL and NoSQL databases, API development, and Azure cloud integration. You will collaborate with cross-functional teams to build insightful dashboards, APIs, and data-driven solutions tailored to our stakeholders' needs.

Key Responsibilities :

1. Design and develop robust, scalable, and secure backend applications using Python with Flask or Django frameworks.

2. Design, maintain, and optimize MySQL databases, including schema creation, query optimization, and ensuring data integrity.

3. Write and optimize complex SQL queries involving joins, aggregations, and subqueries for efficient data retrieval.

4. Utilize Azure Table Storage to store and retrieve structured NoSQL data at scale.

5. Perform CRUD operations on Azure Table Storage using Python libraries like azure-data-tables.

6. Design and manage NoSQL databases using MongoDB, interacting with collections via pymongo for efficient data storage and querying.

7. Develop and deploy RESTful APIs to enable secure, efficient, and scalable data access across platforms.

8. Ensure APIs adhere to industry standards, handling large datasets while maintaining high performance and security.

9. Develop Python scripts to extract and transform data from diverse sources, including databases, APIs, and flat files.

10. Handle and process JSON data structures for seamless storage and API integration.

11. Leverage Azure services like Azure Data Lake, Azure SQL Database, and Azure Databricks to manage and process data.

12. Establish secure connections to Azure Kubernetes Service (AKS) using Python libraries like azure-mgmt-containerservice or kubernetes-python-client.

13. Authenticate and interact with Azure Container Registry (ACR) using Python SDKs or Azure CLI commands.

15. Monitor, identify, and resolve application performance bottlenecks, ensuring reliable and efficient backend services under heavy data loads.