Senior Backend Engineer

2 weeks ago

Shimoga, India DIMAAG Full time

Role Summary We are looking for a skilled Senior Backend Engineer with 3-8 years of professional experience in developing scalable web applications and backend services. The ideal candidate will have strong expertise in FastAPI, along with experience in database design, CI/CD, and cloud environments. Roles & Responsibilities - Design, develop, and maintain scalable backend services and APIs using FastAPI. - Develop and optimize web applications with a strong focus on performance, reliability, and security. - Design and manage relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB). - Collaborate with frontend, DevOps, product, and data science teams to deliver end-to-end solutions. - Integrate machine learning models and background task queues (e.g., Celery, Redis, RabbitMQ) into production systems. - Ensure high code quality through unit and integration testing (e.g., PyTest), peer reviews, and best practices. - Troubleshoot and resolve issues in development and production environments. - Implement CI/CD pipelines, manage deployments, and work closely with DevOps on automation. - Write and maintain technical documentation for APIs, services, and system workflows. Required Skills & Qualifications - 3-8 years of professional experience in backend/full stack development with Python. - Bachelor's or Master's degree in Computer science engineering, IT, or related field. - Hands-on experience with FastAPI (preferred), Flask, and/or Django in production environments. - Proficiency in designing and consuming RESTful APIs. - Strong database experience with SQL (PostgreSQL, MySQL) and familiarity with NoSQL (MongoDB). - Experience with Git/GitHub, Docker, and CI/CD pipelines. - Good understanding of asynchronous programming in Python. Good to Have - Experience with Redis, Celery, or other background task queues. - Knowledge of GraphQL, WebSockets, microservices architecture. - Familiarity with Kubernetes or other container orchestration tools. - Exposure to cloud platforms such as AWS, GCP, or Azure. - Familiarity with real time stream processing and AI pipelines - Understanding of data science workflows, statistics, or mathematics concepts.

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