How to Hire a Django Developer: What to Test in 2026

To hire a Django developer, screen for four things: whether they can predict the SQL their ORM code produces, whether they know which Django version belongs on a new project, whether they treat production settings as a security surface, and whether they can say what actually runs background jobs. A candidate who handles all four will be productive in a week. One who handles none of them can still pass a generic coding interview.

Django is a mature framework, which cuts both ways. Almost any Python developer can build a working Django app, so a portfolio proves little. What separates people is what happens when the app has 40 tables, a million rows and a deploy on Friday.

Start with the version question

Ask: “Which Django version would you start a new project on, and why?” It takes two minutes. The answer shows whether the candidate follows the framework or just uses it.

The official download page lists the current picture. Django 5.2 is a long-term support (LTS) release with extended security support until April 2028. Django 6.0 is a regular release, 6.1 (released August 5, 2026) is the newest, and 6.2, the next LTS, is scheduled for April 2027.

Series	Type	Extended support ends
5.2	LTS	April 2028
6.0	Regular	April 2027
6.1	Regular	December 2027

A strong answer picks a side and gives a reason. “5.2 LTS, because the client wants to upgrade once every two years” is good. “6.1, and we plan to move to the 6.2 LTS next spring” is also good. “Whatever is on PyPI” is not wrong, but it shows nobody has thought about the upgrade bill.

Python versions matter here too. Per Django’s FAQ, 6.1 supports Python 3.12 to 3.14 (3.15 is added in a later patch release), while 5.2 still runs on 3.10. If your servers are on Python 3.10, the Django 6.x series is not available to you yet. A developer should notice that without being told.

Test the ORM, not the syntax

Nearly every slow Django page traces back to the same cause: the template or serializer touches a related object inside a loop, and the ORM runs one query per row.

Give the candidate this and ask what is wrong:

# views.py
def book_list(request):
    books = Book.objects.all()
    return render(request, "books.html", {"books": books})

# books.html
# {% for book in books %}
#   {{ book.title }} by {{ book.author.name }}
# {% endfor %}

One query for the books, then one more for every author. Fifty books means 51 queries. The classic fixes come straight from the QuerySet docs: select_related("author") joins the author in the same query (it works for foreign keys and one-to-one), and prefetch_related runs one extra batch query and joins in Python, which is what you need for many-to-many.

Then ask the follow-up that separates people who read release notes. Django 6.1 added QuerySet.fetch_mode():

from django.db import models

books = Book.objects.fetch_mode(models.FETCH_PEERS)
for book in books:
    print(book.author.name)  # two queries total

FETCH_PEERS loads the missing field for every instance from the same queryset on first access, and FETCH_RAISE throws FieldFetchBlocked so a hot code path fails loudly instead of quietly running queries. Nobody has years of experience with a feature that shipped this summer, so do not penalize a candidate for not knowing it. Watch what they do when you describe it. A good developer immediately asks where they would turn on FETCH_RAISE (tests and critical endpoints), which tells you they think in terms of guarding performance.

For more on the feature itself, see our write-up of Django 6.1’s fetch modes and database-level deletes.

Check how they handle production settings

Django’s own deployment checklist is blunt: “You must never enable debug in production,” because debug mode leaks source excerpts, local variables and settings. It also says SECRET_KEY must be a large random value kept secret, and that ALLOWED_HOSTS needs a real value once DEBUG = False. Sites with user logins should serve everything over HTTPS and set CSRF_COOKIE_SECURE and SESSION_COOKIE_SECURE.

Ask the candidate to walk you through what they check before the first production deploy. The right answer includes python manage.py check --deploy run against production settings, secrets loaded from the environment instead of committed, and a plan for rotating the secret key (Django supports SECRET_KEY_FALLBACKS for that).

Red flag: a candidate whose answer is “set DEBUG to False.” That is one item on a much longer checklist.

Probe migrations and the database

Migrations are where Django projects get hurt. Ask: “How do you add a non-null column to a table with ten million rows without locking it?” You do not need an exact recipe. You want to hear the shape of one: add the column as nullable, backfill in batches, then add the constraint, with the steps split across deploys.

Also ask whether they have read a query plan. QuerySet.explain() exists for this, and a developer who has never used it is probably guessing at indexes.

Database support has a hiring consequence too. Django 6.1 dropped support for PostgreSQL 14, so a project on that version needs a database upgrade before a framework upgrade. The same developer who plans the Django bump should know that, and our PostgreSQL 14 end-of-life guide covers the database half.

Ask what runs the background jobs

Django 6.0 added a built-in Tasks framework: a @task decorator and enqueue(). But the release notes are explicit that Django “does not provide a worker mechanism.” The two built-in backends are meant for development and testing, so production execution is handled by external infrastructure.

So ask: “Where do emails and report exports run in this app?” A good candidate names a real answer (Celery with Redis, a database-backed queue, a cloud queue) and can explain what happens when a job fails halfway. Retry safety, meaning whether running the job twice causes harm, is the question to push on. If you are weighing the options yourself, we compared them in Django 6.0’s Tasks framework versus Celery.

Run a code-review screen

Skip the algorithm puzzle. Prepare a small Django app of about 200 lines with six planted problems: an N+1 in a list view, a view missing a permission check, DEBUG = True in the settings file, a hard-coded secret, a migration that adds a non-null column without a default, and a task that is not safe to retry. Give the candidate 45 minutes and ask them to review it as if it were a pull request.

Score them on what they find, what they rank as most urgent, and how they word the feedback. This mirrors the actual job and fits the approach in our developer screening rubric. For the one or two finalists, a paid trial project is the strongest evidence you can buy.

Django developer or Python developer?

A Django developer is a Python developer with framework depth, so the broader role-definition questions in our guide to hiring a Python developer still apply. Decide first whether you need web backend work, data or ML, or scripting and automation. Many Python developers have touched Django, but touching it and shipping it are different levels.

If the role includes building an API for a separate frontend, add Django REST Framework to the screen, and check that the candidate can explain when they would pick it over FastAPI. We cover that decision in DRF versus FastAPI.

What to pay and where to look

Rates depend mostly on seniority and region, and a framework label moves them less than the gap between a junior and a senior does. Our breakdown of what it costs to hire a developer has the ranges, and the same logic applies here.

For sourcing, the Django community has its own channels: the Django forum, DjangoCon talks and the contributor list in release notes. Open-source contributions to Django or its major packages are a real signal, because the review standards are high. Companies that would rather not run the search themselves can look at CoderCops’ hiring platform.

The short version

Hire for judgment about the four failure points, not for a list of packages. Ask the version question, hand over the N+1 view, ask what runs the jobs and have them review a flawed app. A candidate who does well on those will learn your codebase quickly, and one who does badly will cost you more in production than the interview ever saved.