01Owns
APIs and contracts
Builds and versions endpoints with validated input, consistent errors and pagination, and keeps the contract documented for the clients that call it.
Hire · Backend and data
Hire Python Developers
Senior Python developers who join your team to own APIs, background jobs, integrations and data pipelines. Before you meet anyone, they have completed a paid exercise in the framework you already run, covering slow queries, async code and jobs that are safe to retry.
Tested in your framework, not a generic quiz
Senior and lead levels only
Works inside your services and review
On your team
What a Python developer owns on your team.
02Owns
Background jobs
Moves slow and unreliable work such as emails, imports and third-party calls into queued jobs that retry safely and never run twice by accident.
03Owns
Data models and migrations
Designs tables, indexes and constraints, writes reversible migrations and fixes N+1 queries before they reach production.
04Owns
Integrations
Connects payment, messaging, CRM and partner APIs with timeouts, retries, webhooks verification and logging you can trace.
05Owns
Data and automation work
Writes the scripts and pipelines that clean, move and report on data, and hands ML teams a stable way to serve their models.
Hiring a Python developer: decide the job first
Python is used for very different jobs: web APIs, data pipelines, automation and machine learning. Before hiring, decide which of these the role is mostly about. A strong API developer and a strong data engineer share a language but not much else, and a job description that asks for both usually attracts neither.
For backend roles, the signals that matter are how a developer handles databases and failure. Ask how they found and fixed their last slow query, and what happens in their code when a third-party API times out halfway through a job.
Vetting
Skills we test before a Python developer joins.
01Tested
Framework fit
Knows when Django’s admin and ORM save months, when FastAPI’s typed async endpoints are the better match, and can explain the trade-off for your product.
02Tested
Async and concurrency
Spots blocking calls inside async code, uses task queues for work that should not hold a request, and understands the limits of threads in CPython.
03Tested
Query performance
Reads query plans, removes N+1 patterns with select_related or joins, and adds indexes for the queries that actually run.
04Tested
Typing and tooling
Type hints checked by mypy or pyright, formatting and linting with ruff, and pytest with fixtures that keep tests fast.
05Tested
Packaging and environments
Pinned dependencies with uv or Poetry, reproducible Docker images and settings that never hard-code secrets.
06Tested
Idempotency and retries
Designs jobs and webhook handlers that can run twice without double-charging or double-sending.
Work sample
How the Python developer work sample runs.
- 01Step 1
Diagnose a slow endpoint
The candidate gets an endpoint, its query log and a test database, finds the N+1 query and fixes it without changing the response.
- 02Step 2
Add a validated endpoint
In your framework of choice they add an endpoint with input validation, clear errors and tests. It takes a few hours, and we pay for them.
- 03Step 3
Make a job safe to retry
Given a background job that sends duplicate emails on retry, they make it idempotent and explain how they would prove it.
- 04Step 4
Walk through a deployment
A short call on how the service is configured, migrated and rolled back, aimed at a product owner rather than an engineer.
Testing judgement, not trivia
Questions about generators or decorators are easy to rehearse. A paid task in your framework shows more: how they validate input, structure errors, write tests and name things. Asking them to make a duplicate-sending job idempotent shows whether they think about retries, which is where many production incidents start.
Levels
Python Developers: what changes at each level.
01Level 1
Senior
Owns endpoints, jobs and integrations within an existing service layout and reviews peers’ changes.
02Level 2
Lead
Sets service boundaries, data models, error handling and testing standards, and leads migrations between frameworks or databases.
03Level 3
Data platform engineer
Owns pipelines, scheduling and data quality checks, and works with analysts and ML teams on what they consume.
Choosing between senior, lead and data platform
If your services and conventions are settled, a senior developer adds capacity quickly. If they are not, or you are splitting a monolith, a lead will set boundaries and standards first. If the work is scheduling, moving and validating data for analysts and models, hire for data platform experience rather than web frameworks.
Other options
When to hire someone other than a Python developer.
01Consider
Your product is a Django monolith
If the work is mostly inside an established Django project and its admin, a Django specialist will be productive sooner.
Open register02Consider
A small, focused web service
For lightweight services and internal tools built on Flask, hire a Flask developer.
Open register03Consider
High-concurrency network services
For services that hold many connections with tight latency targets, a Go developer is often the better fit.
Open registerThe first month
Plan one production change in the first week to prove access, CI and review. Then hand over a slice the developer can own: a set of endpoints, an integration or a pipeline, with its monitoring. Ask for a short note on anything they found fragile along the way; new engineers notice what long-standing teams have stopped seeing.
FAQ
Questions to resolve before the build.
01Django or FastAPI: which should our Python developer use?
Use Django when you need an admin, authentication and a mature ORM quickly. Use FastAPI when the product is an API-first service with typed, async endpoints. We match candidates to the framework you run, or help you choose if you have not started.
02Can your Python developers work with our data science team?
Yes. A common setup is a Python developer turning notebook code into a versioned service with tests, monitoring and an API the product can call.
03Will they work in our existing codebase and deployment?
Yes. The first week covers access, local setup, your conventions and one reviewed change that reaches production through your pipeline.
Works alongside
Roles a Python developer works best alongside.
01Pair with
Data scientists
When models need to move from notebooks into a service with versioning, monitoring and a stable API.
Open register02Pair with
DevOps engineers
For container builds, CI, environments and observability once more than one service is in production.
Open register03Pair with
React developers
To build the interface on top of the API, with the contract agreed before either side starts.
Open registerPrimary sources
References behind this page
Dated official documentation, standards, and research that support the factual claims on this page.
- 01Django documentation: Database access optimization
Official guidance on query performance, including select_related and prefetch_related.
- 02Python documentation: asyncio
Reference for asynchronous I/O in the standard library.
How to read this page
Scope, cost and timeline figures are planning guidance until confirmed in a written proposal. Diagrams and screens are illustrations, not client deliverables, and source-code rights and handover follow the signed agreement. See the delivery process and the full disclaimer.
Next decision
Turn the brief into an accepted product scope.
Define outcomes, constraints, evidence, rights and handover before delivery begins.
Commercial rights, repositories, environments, documentation, acceptance and handover remain contract-defined.