Interviews/Specialty Stacks/Django Developer

Hire Django Developers
who actually ship Django that scales past the tutorial

With EasyEnv we build a fit test for the role. Use it to cut the noise at the top of the funnel, or to go deep on the candidates who matter.

You can even evaluate how this person works with AI. So you hire the engineer who can ship, not the one who looks good in a slide.

Django 5DRFCelery · RedisPostgreSQLLive or take-home

Request a Demo Create a Free Account

Real Linux VM

Not a sandbox

systemd, kernel, full toolchain

Browser-based

Zero install for candidates

One link and they are in

Auto-graded

Pass / fail checks per challenge

Plus the full session replay

A great Django developer reads the SQL the ORM generates before they trust it. The good ones reach for select_related and prefetch_related at the right depth, write migrations that survive a 10M-row table, and pick DRF patterns that age well. EasyEnv hands the candidate a real Django project with an N+1 in a list endpoint.

Inside a live interview

What you see when they work.

Real Django, real ORM, every keystroke recorded.

billing-api

AMS

Billing-api

src

billing.py

auth.py

models.py

tests

test_billing.pyM

test_auth.py

pyproject.toml

README.md

Pybilling.py

from decimal import Decimal

def calculate_total(items: list[dict]) -> Decimal:

# Sum line totals using Decimal for currency precision

total = Decimal("0")

for item in items:

total += Decimal(str(item["price"])) * item["qty"]

return total

candidate@django-workspace:~

alice@dev:~/billing-api$

● mainPython 3.12

Claude · ready

Claude

You

Refactor calculate_total to use Decimal for currency math, and add a test.

Claude

Ask Claude...

Mike

Sam

How it works

Three steps. Zero infra to maintain.

Pick the fit test

Use a ready-made challenge or ask us to build one for your stack. Live, take-home, or both.

Send one link

The candidate clicks. A full Linux workspace boots in their browser. No installs, no VPN, no zoom-share.

Review at 2x

Replay the session, read the auto-graded checks, and decide. Most reviews take under five minutes.

The problem

Why hiring a Django Developer is hard.

Django fluency hides under "I built a CRUD app". The interview has to find the depth.

ORM traps are silent until production. The interview has to surface them.

Migrations are where careers go wrong. Reversible, zero-downtime, indexed.

DRF taste is real. Serializer composition, viewset boundaries, permissions.

The fit test

What we measure for a Django Developer.

Every area runs inside a real production-like workspace. The candidate works in a browser, the session records itself.

ORM and N+1

A list endpoint that fires 50 queries. They use select_related and prefetch_related correctly.

Safe migrations

A migration that locks a 10M-row table. They split into safe steps.

DRF design

A messy viewset with mixed concerns. They split serializers and viewsets cleanly.

Auth and permissions

A permission class that leaks rows. They fix without breaking the API.

Celery integration

A task with retry logic that hides errors. They fix observability.

AI collaboration

Allow AI for refactors and grade whether they ran tests + django_debug_toolbar after.

The stack we put in front of them.

Real tools, pre-installed, accessible from the workspace terminal.

Django 5DRFPostgreSQLRedisCelerydjango-debug-toolbarpytest-djangodrf-spectacularchannelsDjango ORMselect_relatedprefetch_relateddjango-axeswhitenoisegunicornpgbouncer

Sample challenges

What a Django Developer interview looks like.

Pick from our library or ask us to build a challenge for your stack. Each one is a real workspace, not a snippet.

Challenge 01

The list endpoint with 50 queries

Scenario

A DRF list endpoint that loads related users one by one. SQL log is open.

What you learn

Whether they pick select_related versus prefetch_related correctly.

In the workspace

$ ls challenges/

workspace, runbook.md, README.md

candidate has:

· a real Linux box in the browser
· kubectl, docker, terraform, jq, yq
· cluster, repo and cloud creds pre-wired
· auto-checks running in the background

interviewer sees:

· every keystroke + every command
· terminal + screen recording
· auto-graded pass/fail per check

AI in the loop

Score the engineer, and how they work with AI.

AI writes Django ORM that queries the world. EasyEnv records prompts so you see whether the candidate looked at the SQL log after the LLM-suggested refactor.

Allow or block AI per question, not per interview

Full prompt and response history replayed in the review

Score "verifies AI output" as a separate signal

Ready to hire a Django Developer who ships?

Set up your first interview in under an hour. We will help you build a fit test for this role on your stack.

Request a Demo Create a Free Account

Role FAQ

Hiring a Django Developer, answered.

Yes. The workspace ships with a seeded Postgres and pgbouncer.

Yes. A Celery worker with Redis is wired and a broken task can be pre-loaded.

No. The workspace runs in their browser. Terminal, editor, ports and dashboards are all served from the EasyEnv workspace, so candidate setup is zero.

Each challenge has automated checks (did the service come back, did the test pass, did the right log message appear) plus a recording your team can replay. Most reviews take under five minutes.

Yes. AI access is a per-interview setting. Block it for fundamentals, then allow it later in the loop to assess AI collaboration separately.

Interviews/Specialty Stacks/Django Developer

Hire Django Developers
who actually ship Django that scales past the tutorial

With EasyEnv we build a fit test for the role. Use it to cut the noise at the top of the funnel, or to go deep on the candidates who matter.

You can even evaluate how this person works with AI. So you hire the engineer who can ship, not the one who looks good in a slide.

Django 5DRFCelery · RedisPostgreSQLLive or take-home

Request a Demo Create a Free Account

Real Linux VM

Not a sandbox

systemd, kernel, full toolchain

Browser-based

Zero install for candidates

One link and they are in

Auto-graded

Pass / fail checks per challenge

Plus the full session replay

Inside a live interview

What you see when they work.

Real Django, real ORM, every keystroke recorded.

billing-api

AMS

Billing-api

src

billing.py

auth.py

models.py

tests

test_billing.pyM

test_auth.py

pyproject.toml

README.md

Pybilling.py

from decimal import Decimal

def calculate_total(items: list[dict]) -> Decimal:

# Sum line totals using Decimal for currency precision

total = Decimal("0")

for item in items:

total += Decimal(str(item["price"])) * item["qty"]

return total

candidate@django-workspace:~

alice@dev:~/billing-api$

● mainPython 3.12

Claude · ready

Claude

You

Refactor calculate_total to use Decimal for currency math, and add a test.

Claude

Ask Claude...

Mike

Sam

How it works

Three steps. Zero infra to maintain.

Pick the fit test

Use a ready-made challenge or ask us to build one for your stack. Live, take-home, or both.

Send one link

The candidate clicks. A full Linux workspace boots in their browser. No installs, no VPN, no zoom-share.

Review at 2x

Replay the session, read the auto-graded checks, and decide. Most reviews take under five minutes.

The problem

Why hiring a Django Developer is hard.

Django fluency hides under "I built a CRUD app". The interview has to find the depth.

ORM traps are silent until production. The interview has to surface them.

Migrations are where careers go wrong. Reversible, zero-downtime, indexed.

DRF taste is real. Serializer composition, viewset boundaries, permissions.

The fit test

What we measure for a Django Developer.

Every area runs inside a real production-like workspace. The candidate works in a browser, the session records itself.

ORM and N+1

A list endpoint that fires 50 queries. They use select_related and prefetch_related correctly.

Safe migrations

A migration that locks a 10M-row table. They split into safe steps.

DRF design

A messy viewset with mixed concerns. They split serializers and viewsets cleanly.

Auth and permissions

A permission class that leaks rows. They fix without breaking the API.

Celery integration

A task with retry logic that hides errors. They fix observability.

AI collaboration

Allow AI for refactors and grade whether they ran tests + django_debug_toolbar after.

The stack we put in front of them.

Real tools, pre-installed, accessible from the workspace terminal.

Django 5DRFPostgreSQLRedisCelerydjango-debug-toolbarpytest-djangodrf-spectacularchannelsDjango ORMselect_relatedprefetch_relateddjango-axeswhitenoisegunicornpgbouncer

Sample challenges

What a Django Developer interview looks like.

Pick from our library or ask us to build a challenge for your stack. Each one is a real workspace, not a snippet.

Challenge 01

The list endpoint with 50 queries

Scenario

A DRF list endpoint that loads related users one by one. SQL log is open.

What you learn

Whether they pick select_related versus prefetch_related correctly.

In the workspace

$ ls challenges/

workspace, runbook.md, README.md

candidate has:

· a real Linux box in the browser
· kubectl, docker, terraform, jq, yq
· cluster, repo and cloud creds pre-wired
· auto-checks running in the background

interviewer sees:

· every keystroke + every command
· terminal + screen recording
· auto-graded pass/fail per check

AI in the loop

Score the engineer, and how they work with AI.

AI writes Django ORM that queries the world. EasyEnv records prompts so you see whether the candidate looked at the SQL log after the LLM-suggested refactor.

Allow or block AI per question, not per interview

Full prompt and response history replayed in the review

Score "verifies AI output" as a separate signal

Ready to hire a Django Developer who ships?

Set up your first interview in under an hour. We will help you build a fit test for this role on your stack.

Request a Demo Create a Free Account

Role FAQ

Hiring a Django Developer, answered.

Yes. The workspace ships with a seeded Postgres and pgbouncer.

Yes. A Celery worker with Redis is wired and a broken task can be pre-loaded.

No. The workspace runs in their browser. Terminal, editor, ports and dashboards are all served from the EasyEnv workspace, so candidate setup is zero.

Each challenge has automated checks (did the service come back, did the test pass, did the right log message appear) plus a recording your team can replay. Most reviews take under five minutes.

Yes. AI access is a per-interview setting. Block it for fundamentals, then allow it later in the loop to assess AI collaboration separately.

How to Hire a Django Developer | ORM · DRF Interviews | EasyEnv | EasyEnv

Hire Django Developerswho actually ship Django that scales past the tutorial

What you see when they work.

Three steps. Zero infra to maintain.

Pick the fit test

Send one link

Review at 2x

Why hiring a Django Developer is hard.

What we measure for a Django Developer.

ORM and N+1

Safe migrations

DRF design

Auth and permissions

Celery integration

AI collaboration

The stack we put in front of them.

What a Django Developer interview looks like.

The list endpoint with 50 queries

Score the engineer, and how they work with AI.

Ready to hire a Django Developer who ships?

Hiring a Django Developer, answered.

Hire Django Developerswho actually ship Django that scales past the tutorial

What you see when they work.

Three steps. Zero infra to maintain.

Pick the fit test

Send one link

Review at 2x

Why hiring a Django Developer is hard.

What we measure for a Django Developer.

ORM and N+1

Safe migrations

DRF design

Auth and permissions

Celery integration

AI collaboration

The stack we put in front of them.

What a Django Developer interview looks like.

The list endpoint with 50 queries

Score the engineer, and how they work with AI.

Ready to hire a Django Developer who ships?

Hiring a Django Developer, answered.

Hire Django Developers
who actually ship Django that scales past the tutorial

Hire Django Developers
who actually ship Django that scales past the tutorial