Python Software Developer

As a Python and SQL-based Backend/Data Engineer, you will be responsible for: - Designing, developing, testing, and deploying high-quality Python-based applications and services. - Building and maintaining scalable backend systems and RESTful APIs. - Working with Python frameworks such as Django, Flask, or FastAPI. - Writing clean, effective, reusable, and testable code with proper unit test coverage. - Designing and implementing complex SQL queries, stored procedures, and database solutions. - Performing database design, data modeling, and migration tasks. - Working with relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB). - Developing data pipelines and automating workflows using Python. - Optimizing applications and APIs for performance, scalability, and reliability. - Working with microservices architecture and API integrations. - Leveraging cloud platforms (AWS/Azure/GCP) for building and deploying applications. - Utilizing messaging/streaming tools such as Kafka or RabbitMQ. - Ensuring data integrity, security, and efficient data retrieval. - Exposure to AI-assisted development tools (GitHub Copilot). - Working with modern AI/ML ecosystems (LLMs, LangChain, vector DBs like Pinecone/FAISS/Weaviate). - Collaborating with cross-functional teams (UI, product, DevOps). - Mentoring junior developers and conducting code reviews. - Participating in Agile/Scrum ceremonies and delivering solutions based on user stories. - Troubleshooting, debugging, and solving complex technical problems. Qualifications Required: - Strong proficiency in Python for backend development and data engineering. - Expertise in SQL and database programming (PL/SQL preferred). - Experience with RESTful API development and microservices architecture. - Hands-on experience with relational and NoSQL databases. - Familiarity with cloud platforms (AWS/Azure/GCP). - Knowledge of messaging systems like Kafka or RabbitMQ. - Understanding of scalable, distributed systems and performance optimization. - Experience with unit testing frameworks and test-driven development. - Exposure to CI/CD pipelines and DevOps practices. - Familiarity with AI/ML tools, LLMs, or vector databases is a plus. As a Python and SQL-based Backend/Data Engineer, you will be responsible for: - Designing, developing, testing, and deploying high-quality Python-based applications and services. - Building and maintaining scalable backend systems and RESTful APIs. - Working with Python frameworks such as Django, Flask, or FastAPI. - Writing clean, effective, reusable, and testable code with proper unit test coverage. - Designing and implementing complex SQL queries, stored procedures, and database solutions. - Performing database design, data modeling, and migration tasks. - Working with relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB). - Developing data pipelines and automating workflows using Python. - Optimizing applications and APIs for performance, scalability, and reliability. - Working with microservices architecture and API integrations. - Leveraging cloud platforms (AWS/Azure/GCP) for building and deploying applications. - Utilizing messaging/streaming tools such as Kafka or RabbitMQ. - Ensuring data integrity, security, and efficient data retrieval. - Exposure to AI-assisted development tools (GitHub Copilot). - Working with modern AI/ML ecosystems (LLMs, LangChain, vector DBs like Pinecone/FAISS/Weaviate). - Collaborating with cross-functional teams (UI, product, DevOps). - Mentoring junior developers and conducting code reviews. - Participating in Agile/Scrum ceremonies and delivering solutions based on user stories. - Troubleshooting, debugging, and solving complex technical problems. Qualifications Required: - Strong proficiency in Python for backend development and data engineering. - Expertise in SQL and database programming (PL/SQL preferred). - Experience with RESTful API development and microservices architecture. - Hands-on experience with relational and NoSQL databases. - Familiarity with cloud platforms (AWS/Azure/GCP). - Knowledge of messaging systems like Kafka or RabbitMQ. - Understanding of scalable, distributed systems and performance optimization. - Experience with unit testing frameworks and test-driven development. - Exposure to CI/CD pipelines and DevOps practices. - Familiarity with AI/ML tools, LLMs, or vector databases is a plus.