Hire Python Developers — Django, FastAPI & Data Engineering
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Hire Python Developers — Backends, APIs & Data Engineering
Python is the dominant backend language for web APIs, data engineering, and ML integration. CimpleO builds Python backends for product companies and data-intensive applications — clean Django and FastAPI services, data pipelines, and ML integration layers that your team can maintain.
What We Build
REST & GraphQL APIs FastAPI services with OpenAPI documentation, Pydantic validation, async handlers, and JWT/OAuth2 auth. Django REST Framework APIs with serialisers, viewsets, and permission classes. Both built with versioning, rate limiting, and the error handling your frontend and mobile teams can depend on.
Django Web Applications Full-featured web applications with Django’s ORM, admin interface, and ecosystem. Multi-tenant architectures, custom user models, complex permission systems, Celery task queues, and Channels for WebSocket support. We build Django applications that are maintainable at scale — not flat views.py files.
Data Pipelines & ETL Apache Airflow or Prefect for orchestrated data pipelines. Data ingestion from APIs, databases, files, and event streams. Transformation with Pandas or Polars (for large datasets). Output to PostgreSQL, data warehouses (BigQuery, Snowflake, Redshift), or data lakes (S3 + Parquet). We’ve built pipelines processing millions of records daily.
Background Task Systems Celery with Redis or RabbitMQ for asynchronous task processing: email/SMS sending, PDF generation, webhook delivery, image processing, report generation, and third-party API calls that shouldn’t block request-response cycles. Beat schedules for periodic jobs.
Automation & Scripting One-off and recurring automation: data migration scripts, reporting automation, API scraping, document processing, and system integration glue. We write scripts that are readable, logged, and handle errors — not one-liners that break silently.
ML Model Integration Serving scikit-learn, TensorFlow, and PyTorch models via FastAPI endpoints. Model versioning, A/B testing routing, prediction logging, and monitoring for model drift. If you need the models trained (not just served), see Hire AI/ML Engineers.
Tech Stack
- Web frameworks: Django 4.x, FastAPI, Flask, Starlette
- API: Django REST Framework, Pydantic, GraphQL (Strawberry, Graphene)
- Async: asyncio, HTTPX, aiohttp, Channels (Django)
- Task queues: Celery, RQ, Dramatiq, Arq
- Data: Pandas, Polars, NumPy, Apache Airflow, Prefect
- ORM/Database: Django ORM, SQLAlchemy, Alembic, psycopg2, asyncpg
- Testing: pytest, Factory Boy, pytest-django, HTTPX, Hypothesis
- DevOps: Docker, uv/Poetry, GitHub Actions, AWS Lambda, Gunicorn, Uvicorn
Engagement Models
Fixed-scope API or backend project: defined deliverables, fixed price. Right for greenfield services with clear requirements.
Dedicated Python engineer: monthly retainer. Right for ongoing backend development, feature additions, and technical debt reduction.
Code audit & refactor: assessment of existing Python backend with a prioritised remediation plan and implementation.
Related Services
For full-stack web development (Python backend + React frontend), see Web Development Services. For Python-based AI/ML engineering, see AI/ML Development.
Get a Scope
Tell us your framework preference (or lack of one), the type of backend you need, and your timeline. We’ll respond within 24 hours.
Frequently Asked Questions
Django, FastAPI, or Flask — which should we use?
Django for full-featured web applications and CMS-style products — batteries included, ORM, admin, auth, and a mature ecosystem. FastAPI for high-performance API services where async throughput matters, type safety is a priority, and you don't need Django's full admin stack. Flask for simple APIs or microservices where you want minimal framework overhead. We recommend based on your specific requirements — we build with all three.
How much does Python backend development cost?
A simple REST API with auth and basic CRUD: $10,000–$25,000. A Django web application with admin panel, business logic, and integrations: $25,000–$80,000. A data pipeline or ML integration backend: $20,000–$60,000. Dedicated Python engineer retainer: from $7,000/month.
Can you work with our existing Python codebase?
Yes. We join existing Django and FastAPI projects regularly. We assess code quality honestly — if there are parts cheaper to rewrite than extend, we say so with reasoning. We've resolved performance bottlenecks, migrated databases, and refactored spaghetti view logic into clean service layers.
Do you handle database design and ORM setup?
Yes. Django ORM for most Django projects, SQLAlchemy for FastAPI/Flask. We design schemas with query performance in mind from the start — not generic REST CRUD models that create N+1 problems at scale. Migrations with Alembic or Django migrations, designed for zero-downtime deployment.
Can your Python team integrate ML models into our application?
Yes. We integrate ML models (scikit-learn, TensorFlow, PyTorch) via REST API endpoints, background task queues (Celery, RQ), or streaming pipelines. If you need model training and deployment rather than just integration, see our AI/ML engineering service.
Do you write tests?
Yes — pytest for unit and integration tests, Django Test Client or HTTPX for API endpoint testing. We target meaningful coverage of business logic, not 100% coverage of boilerplate. Test infrastructure (fixtures, factories with Factory Boy, CI integration) is included.