Location : Pune (onsite).

About The Role :

We are looking for an experienced Senior Python Developer (3-6 years) to design and scale offline applications, data workflows, and API integrations.

The role requires strong backend engineering expertise, with hands-on experience in workflow automation, third-party API integration, and data processing pipelines.

Key Responsibilities :

- Design and develop automation pipelines and offline applications that integrate with multiple APIs.

- Build and manage data workflows for ingesting, transforming, and exporting data between systems.

- Develop resilient task execution frameworks using asyncio-based workers.

- Integrate with third-party APIs (REST/GraphQL/SDKs) for payments, ads, reporting, and retail systems.

- Work with relational and non-relational databases like PostgreSQL, MySQL, and MongoDB.

- Implement caching strategies using Redis to optimize workflows.

- Ensure workflows are reliable, fault-tolerant, and recoverable.

- Write and maintain unit, integration, and workflow-level tests.

- Collaborate with DevOps teams to deploy automation pipelines on Docker/Kubernetes.

- Conduct performance and load testing using tools like Locust, JMeter, or k6.

- Participate in architecture discussions, code reviews, and technical planning.

Required Skills & Experience :

- 3-6 years of experience in Python development.

- Strong understanding of computer science fundamentals (BE/BTech or MS in CS/IT).

- Hands-on experience with automation scripts, ETL pipelines, or data workflows.

- Proficiency with task queues and schedulers (Celery, RQ, Airflow, APScheduler).

- Strong API integration skills (REST, GraphQL, SDKs).

- Familiarity with asynchronous programming (asyncio, aiohttp).

- Database experience with PostgreSQL/MySQL/MongoDB, including query optimization.

- Experience with Redis for caching and background jobs.

- Knowledge of error handling, retries, and backoff strategies.

- Experience with Git, CI/CD pipelines, Docker, and Kubernetes.

- Understanding of monitoring tools (Prometheus, Grafana, ELK Stack).

- Cloud experience (AWS, GCP, or Azure) for scalable deployments.

- Experience with pytest or unittest for test-driven development.

- Exposure to message queues (Kafka, RabbitMQ, SQS) and event-driven systems.