Job Profile: Python Developer | Duties, Skills, Salary 2026

38-75K EUR

Annual gross salary

Bac+3 to Bac+5

Required training

Technology & IT

Sector

Very high

Market demand

About the role

The Python developer is a professional specialised in the Python programming language, one of the most popular and versatile worldwide. Capable of working on web projects, data science, artificial intelligence, automation or DevOps, they're among the most sought-after IT profiles.

The role is experiencing strong growth with the explosion of generative AI, machine learning and data analysis. Python developers experienced in AI are particularly sought after with +10-15% salary increase versus 2024.

Python 3.12 and 3.13 bring significant performance improvements (20-30% faster). The AI/ML ecosystem continues to explode with LangChain, LlamaIndex and new models.

Web application development

Design and develop web apps with Django, FastAPI or Flask. Create performant REST or GraphQL APIs. Implement authentication, authorisation and security. Optimise performance and scalability.

Data science and machine learning

Process and analyse data with pandas, NumPy and Jupyter. Develop ML models with scikit-learn, TensorFlow or PyTorch. Create data processing and ETL pipelines. Visualise data with Matplotlib, Seaborn or Plotly.

Automation and scripting

Automate repetitive tasks and workflows. Develop file processing and web scraping scripts (BeautifulSoup, Scrapy). Create CLI tools (Click, Typer). Integrate third-party systems via their APIs.

Database management

Interact with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis) databases. Use ORMs (SQLAlchemy, Django ORM, Tortoise). Optimise queries and performance. Manage schema migrations.

Testing and code quality

Write unit tests (pytest, unittest) and integration tests. Follow PEP (Python Enhancement Proposals). Use linters (pylint, flake8, ruff) and formatters (black, isort). Document code with docstrings and Sphinx.

DevOps and deployment

Containerise apps with Docker. Configure CI/CD pipelines (GitHub Actions, GitLab CI). Deploy to cloud (AWS Lambda, Google Cloud Run, Azure Functions). Monitor apps in production (Sentry, New Relic).

Technical skills vs soft skills

Avantages

Advanced mastery of Python 3.11+ and modern features
Expertise in at least one web framework (Django, FastAPI, Flask)
In-depth knowledge of data libraries (pandas, NumPy, Jupyter)
Mastery of SQL and NoSQL databases
Knowledge of machine learning and AI (scikit-learn, TensorFlow, PyTorch)
Mastery of testing tools (pytest, unittest, coverage)
DevOps knowledge (Docker, CI/CD, cloud computing)

Inconvénients

Rigour and attention to detail
Analytical and problem-solving ability
Curiosity and continuous technology watch
Autonomy and proactivity
Communication and teamwork
Sense of optimisation and performance

Django vs FastAPI comparison

Django vs FastAPI

Critère	Django	FastAPI
Maturity	15+ years (mature, stable)	Recent (modern, fast-growing)
Built-in features	ORM, admin, auth (batteries included)	Minimal (pick your tools)
Performance	Good	Excellent
Learning curve	Moderate	Gentle
Community/Jobs	Larger, more job offers	Growing, trending

Salary scale 2026

Python developer salaries by experience (gross annual)

Experience	Startup/SME	Mid-size company	Large company	London/SE
Junior (0-2 years)	36-43K EUR	40-48K EUR	45-55K EUR	+10-15%
Experienced (2-5 years)	43-58K EUR	50-65K EUR	55-75K EUR	+10-15%
Senior (5-10 years)	58-72K EUR	65-85K EUR	75-100K EUR	+15-20%
Lead / Architect (10+ years)	70-95K EUR	85-120K EUR	100-150K EUR	+20-25%

Training and careers

Becoming a Python developer

Level	Qualification	Outcomes
Bac+2	BTEC Higher National Certificate, Higher National Diploma	Junior Python developer
Bac+3	Foundation Degree, BSc Computer Science (incomplete)	Junior Python developer
Bac+5	BSc Computer Science, Engineering degree	Senior Python developer, Lead dev
Bootcamp	Le Wagon, General Assembly, DataCamp (3-6 months)	Career change to Python development

Career progression

0-2 years

Junior Python developer

Script development, feature implementation

2-5 years

Python developer

Full autonomy, API development, data processing

5-10 years

Senior Python developer

Architecture decisions, ML projects, mentoring

10+ years

Lead Python developer

Technical leadership, team management

12+ years

Data Science Lead / AI Architect

AI/ML strategy, large-scale projects

Frequently asked questions about Python developers

What's the difference between a Python backend developer and a data scientist?

The Python backend developer focuses on building scalable web applications and APIs using frameworks like Django or FastAPI. The data scientist uses Python for data analysis, statistical modelling and machine learning. There's overlap: both use Python, but their focus, tools and skills differ significantly. A backend dev might work with AI, and a data scientist might deploy models.

Can a Python developer specialise in AI/ML?

Yes, increasingly common. Python dominates AI/ML with libraries like TensorFlow, PyTorch, scikit-learn. A Python developer can specialise in machine learning engineering, building ML pipelines and production systems. AI/ML specialists are highly valued with premium salaries (+20-30% vs standard Python developers).

Should a Python developer also know a frontend framework?

Not essential, but useful. Many Python developers become full-stack by learning JavaScript and a frontend framework (React, Vue.js). This opens more opportunities and positions for full-stack developer roles with better salaries. For backend-focused roles, frontend knowledge is not required.

What makes a Python developer junior vs senior?

Junior: understands Python basics, can implement simple features with guidance. Mid-level: autonomous on feature development, understands architecture, can mentor juniors. Senior: designs systems, makes technology choices, deep expertise in Python and chosen speciality (backend, data, DevOps). Experience, problem-solving ability and mentoring capacity differentiate levels.

Is Python slow? Does performance matter for Python developers?

Python is slower than compiled languages, but for web apps and data processing, it's usually fast enough. Performance matters, especially for data processing and ML. Good Python developers optimise code, use compiled libraries (NumPy, Pandas), and know when to use other technologies. Understanding performance characteristics and bottlenecks is part of professional development.

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