Python Panda - Engineer

Key Responsibilities:

Backend Development:

• Design, develop, and maintain scalable Python applications using Pandas for data processing.


• Build and integrate RESTful APIs and microservices in a service-oriented architecture.


• Write efficient Python scripts for automation, data transformation, and backend logic.

Frontend Development:

• Collaborate with UI/UX designers to implement responsive and dynamic user interfaces using Angular and JavaScript.


• Ensure seamless integration between frontend and backend components.

Database Management:

• Design and optimize SQL queries and stored procedures.


• Work with relational databases (e.g., SQL Server) for data storage and retrieval.


• Perform data modeling and schema design to support application requirements.

Architecture & Design:

• Contribute to architectural decisions and system design discussions.


• Ensure code quality, scalability, and maintainability through best practices and code reviews.

Collaboration & Agile Practices:

• Work closely with cross-functional teams including product managers, QA engineers, and DevOps.


• Participate in Agile ceremonies (daily stand-ups, sprint planning, retrospectives).


• Document technical specifications and maintain project documentation.

Required Skills & Qualifications:

• 5+ years of professional experience in Python development.


• Strong expertise in Pandas for data manipulation and analysis.


• Solid understanding of service-based and microservices architecture.


• Proficiency in Python scripting for automation and backend tasks.


• Working knowledge of Angular (16+) and JavaScript for frontend development.


• Experience with SQL databases and writing complex queries.


• Familiarity with version control systems (e.g., Git).


• Excellent problem-solving and communication skills.

Preferred Qualifications:

• Experience with cloud platforms (Azure, GCP).


• Knowledge of containerization tools (Docker, Kubernetes).


• Exposure to CI/CD pipelines and DevOps practices.


• Understanding of data visualization tools or libraries.