Senior Product Developer

4 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

About The Role

We are looking for a strong Python Developer with 4+ years of hands-on experience to build, scale, and optimize backend systems. You will work closely with engineering, product, and data teams to deliver reliable APIs, automation, integrations, and high-performance services.

Key Responsibilities

  • Develop, optimize, and maintain backend services, APIs, and microservices using Python.
  • Build integrations with third-party APIs, REST/GraphQL services, and internal systems.
  • Design clean, maintainable, and scalable code following best practices.
  • Work with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis).
  • Implement data processing pipelines, automation scripts, and background workers.
  • Debug, troubleshoot, and improve existing codebases and application performance.
  • Write unit tests, integration tests, and follow CI/CD practices.
  • Collaborate with product, design, and frontend teams to translate requirements into technical solutions.
  • Participate in code reviews, sprint planning, and architectural discussions.

Required Skills

  • 4+ years of professional experience in Python development.
  • Strong knowledge of Python frameworks such as FastAPI, Django, or Flask.
  • Solid understanding of OOP, data structures, algorithms, and software design patterns.
  • Experience with RESTful API development and API documentation tools (Swagger/OpenAPI).
  • Hands-on experience with PostgreSQL/MySQL, including schema design and query optimization.
  • Familiarity with message queues/job runners (Celery, RabbitMQ, Kafka, Redis).
  • Experience with Git, Docker, and cloud environments (AWS/GCP/Azure).
  • Strong debugging and problem-solving skills.
  • Ability to work independently and deliver clean, production-quality code.

Good to Have

  • Experience with microservices architecture.
  • Knowledge of async programming (asyncio, FastAPI).
  • Experience working with LLMs, vector databases, or AI/ML pipelines.
  • Understanding of caching, performance tuning, and scalability.
  • Exposure to DevOps tools (CI/CD pipelines, monitoring, logging).

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