Backend Developer – Python/Django

We are seeking a highly skilled Backend Developer with strong experience in Python, Django, FastAPI, and modern backend architecture. The role involves designing and scaling data-driven systems, building APIs, and managing data pipelines and asynchronous processing for a high-performance analytics and automation platform.

Design, develop, and maintain backend services and APIs using Python (Django, FastAPI).

Implement a microservices-based architecture for modularity, scalability, and ease of deployment.

Develop data pipelines for ingestion, transformation, and aggregation of large datasets.

Integrate Celery + Redis for task scheduling, background processing, and queue management.

Write and optimize SQL queries and manage database schemas in PostgreSQL or similar relational databases.

Build secure, high-performance REST APIs and collaborate closely with frontend and AI teams.

Set up and maintain Dev/Staging/Prod environments and contribute to CI/CD pipelines.

Ensure system reliability, scalability, and fault tolerance across backend components.

Contribute to code reviews, documentation, and architectural decisions.

2+ years of hands-on backend development experience using Python and Django.

Strong understanding of FastAPI, RESTful API design, and microservice communication patterns.

Experience with Celery for background jobs and Redis for caching and distributed task queues.

Proficiency with PostgreSQL or similar SQL databases, including schema design and query optimization.

Working knowledge of data pipelines, ETL processes, and asynchronous task handling.

Experience with Docker and cloud platforms such as AWS or GCP.

Familiarity with authentication/authorization mechanisms (OAuth, JWT)

Understanding of software architecture principles, version control (Git), and CI/CD workflows.

Exposure to monitoring, logging, and performance optimization tools (e.g., Prometheus, ELK, Sentry).

Experience with GraphQL, Kafka, or RabbitMQ.

Familiarity with data analytics or AI/ML pipeline integration.

Experience integrating third-party APIs or data sources.

Knowledge of infrastructure-as-code tools (Terraform, Ansible, etc.).