Python Developer _Engineer (1-4 Years)
Role Overview
As a Python Developer, you will design, develop, and maintain scalable backend systems and APIs using Python. You will work in a consulting environment, collaborating with cross-functional teams (business analysts, front-end developers, DevOps/SRE, data engineers) to deliver high-impact solutions for clients across industries.
Key Responsibilities
- Design, code, test, deploy and maintain backend services and APIs using Python and frameworks such as Django, Flask or FastAPI.
- Work with relational (PostgreSQL, MySQL, SQL Server) and/or NoSQL (MongoDB, Redis) databases.
- Build and maintain data pipelines: ingesting, transforming, and serving large data sets (Pandas, NumPy, PySpark).
- Write unit tests, integration tests (pytest/unittest) and ensure code quality, maintainability and performance.
- Participating in agile ceremonies: sprint planning, daily stand-ups, retrospectives.
- Communicate technical concepts effectively to stakeholders and help translate business requirements into technical solutions.
Requirements
Required / Must-Have Skills
- Strong proficiency in Python (Python 3.x) with solid understanding of language features, data structures, OOPS and async programming.
- Experience with one or more web/back-end frameworks: Django, Flask, FastAPI.
- Experience building RESTful APIs, working with JSON, serialization, authentication/authorization.
- Hands-on with unit testing frameworks (pytest, unittest), debugging and writing maintainable code.
- Familiarity with database systems (SQL and/or NoSQL), writing complex queries, and working with schema design.
- Knowledge of version control systems (Git) and software development best practices.
- Good problem-solving skills and ability to work collaboratively in a team environment.
- Bachelor's degree in computer science, Engineering or related discipline (or equivalent experience).
Preferred / Nice-to-Have Skills
- Experience with Python programming.
- Experience with big data/distributed processing (PySpark, Spark, etc).
- Exposure to data science/ML libraries (pandas, NumPy, scikit-learn) and analytics workflows.
- Understanding of microservices architecture, system design, performance tuning and scalability.
- Good communication skills to interact with clients and business stakeholders.
