Senior Backend Engineer

17 hours ago

Bangalore, 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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