The same Python developer might spend Monday on a Django admin screen for the finance team, Tuesday on a FastAPI endpoint for the mobile app, and Wednesday on a Celery job that pulls supplier price files every night and cleans them before import. Python is used for so many kinds of work that the title alone tells a candidate very little, which is exactly why the job description has to say which kind you mean.
This page gives you a Python developer job description ready to copy, then explains how the role changes from junior to senior, which skills to test and how, the mistakes that attract the wrong applicants, and how to choose between contract and permanent hiring.
Python developer job description template
Swap the bracketed text for your details. If the role is mostly data processing or mostly web, delete the lines that do not fit.
About the role
[Company] is hiring a Python Developer to build and maintain the backend of [product / internal platform]. You will work mainly in [Django / FastAPI / Flask], writing web services, background jobs and integrations with [partner systems, payment providers, internal tools]. You will be part of a [team size] engineering team based in [city / remote], working with product owners and other developers.
Responsibilities
- Build and maintain web backends and APIs in [Django / FastAPI / Flask], including models, views or routes, and serializers or schemas.
- Write background and scheduled jobs with Celery [or RQ], with retries and idempotency so a rerun does no harm.
- Build integrations with third-party APIs and files, such as CSV and Excel imports, webhooks and partner feeds.
- Write data processing and automation scripts that replace manual work for other teams.
- Use type hints throughout and keep mypy or a similar checker passing.
- Write tests with pytest, using fixtures and factories, and keep coverage meaningful rather than cosmetic.
- Use async Python where it clearly helps, such as many slow outbound calls, and keep synchronous code where it does not.
- Manage dependencies and virtual environments cleanly with [Poetry / uv / pip-tools].
- Profile and fix slow code and slow ORM queries, including N+1 query problems.
- Review pull requests and keep the codebase readable for the next developer.
Requirements
- [X]+ years writing Python professionally, beyond scripting or coursework.
- Production experience with at least one of Django, FastAPI or Flask.
- Good knowledge of SQL and an ORM such as the Django ORM or SQLAlchemy, with PostgreSQL or a similar database.
- Experience writing tests with pytest or unittest.
- Understanding of Python’s own behaviour: mutability, generators, context managers, the GIL and what it means for concurrency.
- Experience with Git and code review.
- Ability to explain technical choices in plain English to non-developers.
Nice to have
- Experience with pandas or Polars for data cleaning and transformation.
- Experience with Celery and Redis or RabbitMQ in production.
- Familiarity with Docker and deploying Python services on AWS.
- Experience with Pydantic models for validation.
What we offer
- [Salary range].
- [Work mode: remote, hybrid, on-site].
- [Benefits and learning support].
How the Python developer role changes by level
Junior Python developer. Writes clear Python inside an existing framework setup: a new view, a new model field, a script to fix some data. The job description should ask for fluent core Python and familiarity with one framework, and should mention that they will learn testing and deployment from the team. Avoid asking juniors for async and Celery as must-haves.
Mid-level Python developer. Owns a service or a set of jobs. They decide how a background task should retry, how to structure a Django app so it stays maintainable, and when to drop the ORM for raw SQL. They write integrations that survive a partner’s API changing without notice. Ask for examples of services they maintained over time, not just built.
Senior Python developer. Sets the standards for the Python codebase: project layout, typing policy, testing approach, dependency upgrades and the move from one major Python or Django version to the next. They pick between Django and FastAPI for new services with reasons, and they help other teams who write Python occasionally, such as analysts. The job description should ask for this kind of influence beyond their own code.
Skills that matter most and how to check them
Python is easy to start and easy to write badly, so the screening should look past whether code runs and into whether it will stay maintainable.
- Idiomatic Python. Hand them a forty-line function written like Java and ask them to clean it up. Good candidates reach for comprehensions, context managers and the standard library without overdoing it.
- ORM awareness. Show a Django or SQLAlchemy loop that triggers a query per row and ask what is wrong. They should spot the N+1 problem and know select_related, prefetch_related or joined loading.
- Background job design. Ask: “A nightly job imports a supplier file and sometimes fails halfway. What happens on the rerun?” Look for idempotency, transactions and clear logging.
- Async judgement. Ask when they would use asyncio and when they would not. A strong candidate explains that async helps with many waiting I/O calls and does nothing for CPU-heavy work.
- Testing. Give them a function that calls an external API and ask how to test it. Expect mocking or a fake client, and fixtures that keep tests fast.
- A small take-home. A short FastAPI or Django task with one endpoint, validation, a background job and tests shows typing, structure and testing habits in one go.
Common Python developer job description mistakes
- Not saying which kind of Python work it is. Web backend, data pipelines, automation and machine learning all use Python but need different people. Fix: state the main type of work in the first line of About the role.
- Listing Django, Flask and FastAPI all as must-haves. Few developers use all three in depth. Fix: name your framework and accept experience in any of the others.
- Mixing in machine learning by accident. Adding TensorFlow or PyTorch “just in case” pulls in data scientists for a web role. Fix: only mention ML libraries if the person will use them.
- Treating scripting experience as enough. Writing one-off scripts is different from maintaining a service. Fix: ask for experience with tests, code review and production deployments.
- Ignoring the Python version. Candidates want to know if they will be on a modern version or maintaining old code. Fix: state the Python and framework versions, especially if an upgrade is part of the job.
Contract, contract-to-hire or permanent
A contract Python developer is a good fit for automation and integration projects with a clear end, such as replacing a manual reporting process, building a partner data feed or upgrading an old Django version. These are well-scoped and benefit from someone who has done them before.
Contract-to-hire suits teams building a new Python service who want to see the developer’s code structure and testing habits on real work before committing to them long term.
Permanent is better when the Python codebase is central to your business and you need someone to own it over years of upgrades and new features. Zilo AI helps companies hire Python developers in India on contract, contract-to-hire or permanent terms. If you are also hiring data engineers or QA, our IT recruitment page lists the other roles we fill.
Frequently asked questions
What should a Python developer job description include?
The kind of Python work (web, data, automation), the framework, the database, how the code is tested and deployed, the level, and the practical details of pay and work mode. Being specific about the type of work matters more for Python than for most languages.
What is the difference between a Python developer and a data engineer?
A Python developer usually builds application backends, APIs and automation. A data engineer builds pipelines and warehouses that move and model data for analytics, often with tools like Spark, Airflow and dbt. They overlap in data processing scripts, but the core work and tools differ.
Should I ask for Django or FastAPI?
Ask for whichever you use. Django suits full applications with an admin panel and lots of standard features; FastAPI suits lighter API services with typed request handling. A good Python developer can move between them, so list the other as a plus rather than a requirement.
Does a Python developer need to know machine learning?
No, unless the job involves training or serving models. Most Python developer roles are backend and automation work, and requiring ML knowledge shrinks your pool without benefit.
If you would like Zilo AI to source and screen Python developers for you, share the framework, the kind of work and the level. Get in touch with Zilo AI and we will take it from there.