KPMG

Senior - Python

Posted On

May 6, 2025

Location

Gurugram, Haryana

Experience Level

KI Professional

Job Type

Full Time

Apply By

June 18, 2025

Job Description

About KPMG in India

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.

KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.

Key Responsibilities:

• Design, develop, and maintain scalable backend systems using Python frameworks such as FastAPI, Django, and Flask.

• Build, deploy, and maintain RESTful APIs to support various front-end and mobile applications.

• Implement asynchronous jobs and background tasks using libraries like Celery, Dramatiq, or RQ.

• Utilize multi-threading and concurrency to optimize backend performance.

• Containerize applications using Docker and deploy to cloud platforms such as AWS, Google Cloud, or Azure.

• Integrate with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Redis).

• Implement CI/CD pipelines for continuous integration, testing, and deployment.

• Collaborate with cross-functional teams, including front-end developers, to ensure smooth and efficient system integration.

• Ensure scalability, security, and high performance in backend systems, optimizing code where necessary.

• Stay informed on the latest technologies and practices in backend development, cloud infrastructure, and data analytics.

• Use data analytics tools to provide insights where needed, utilizing libraries such as Pandas, NumPy, or similar.

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