Senior Python Developer

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.