Hire Pre-vetted Python Developers

What is a Python Developer?

A Python Developer is a software engineer specializing in building applications, systems, and solutions using Python—one of the world's most versatile and in-demand programming languages. Python Developers do far more than write code: they architect scalable backend systems, design robust APIs, build data pipelines that power analytics, and create intelligent applications with machine learning. Whether you need someone to modernize legacy codebases, build production-grade web applications, or automate critical business processes, a skilled Python Developer brings both technical depth and strategic thinking.
What makes Python Developers valuable is their ability to move fast without sacrificing quality. Python's straightforward syntax lets developers focus on solving your business problem rather than wrestling with language complexity. This is why startups and Fortune 500 companies alike trust Python for mission-critical applications. When you hire through Torc, you're getting someone who writes maintainable, scalable code that grows with your business.

Technology Stack

Core Python & Fundamentals

• Python 3.8+, Python 3.10+, Python 3.11+

• Object-Oriented Programming & design patterns

• Functional programming concepts

• Data structures & algorithms

• Version control (Git, GitHub, GitLab)

• Package management (pip, poetry, conda)

Web Frameworks & Backend

• Django—full-featured framework for complex applications

• FastAPI—modern, high-performance APIs with automatic documentation

• Flask—lightweight framework for rapid development and microservices

• SQLAlchemy—advanced ORM for database interaction

• REST API design & implementation

• GraphQL frameworks (Strawberry, Graphene)

• Async/await & asynchronous programming

Data Engineering & Analytics

• Pandas—data manipulation, cleaning, and analysis

• NumPy—numerical computing and array operations

• Scikit-learn—machine learning models and preprocessing

• Apache Spark & PySpark—large-scale data processing

• ETL pipelines & data workflows

• Data warehouse tools (Snowflake, BigQuery integration)

AI & Machine Learning

• TensorFlow & Keras—deep learning and neural networks

• PyTorch—flexible ML framework for research and production

• LLM integration—working with GPT, Claude, fine-tuning

• Computer Vision—image processing and recognition

• NLP—natural language processing and text analysis

• Model deployment & serving

Cloud & DevOps

• AWS—Lambda, EC2, S3, RDS, Serverless services

• Google Cloud Platform—Compute Engine, Cloud Functions

• Azure—App Service, Functions, databases

• Docker—containerization and microservices

• Kubernetes—orchestration and scaling

• CI/CD—GitHub Actions, Jenkins, GitLab CI

Testing & Quality

• Pytest—modern testing framework

• Unit testing, integration testing, functional testing

• Code quality tools—linting, type checking, code coverage

• Mocking & fixtures (unittest.mock, pytest fixtures)

• Performance testing & profiling

Databases & Data

• PostgreSQL & MySQL optimization

• NoSQL databases (MongoDB, Redis)

• Database design & schema optimization

• Query optimization & indexing

• Data modeling & relationships

Key Qualities to Look For on a Python Developer

Problem Solver Great Python developers don't just code—they think critically about your business challenges. They break complex requirements into manageable tasks, propose multiple solutions with trade-offs, and make deliberate architectural choices. They ask the right questions before building, saving time and technical debt down the line.
Clean Code Advocate—they understand that code is read far more often than it's written. Exceptional developers write code that's maintainable, well-documented, and easy for teammates to understand. They follow PEP 8 standards, use meaningful naming conventions, and build testing into their workflow from day one—not as an afterthought.
Full-Stack Thinker—while specialized in Python, they grasp the broader system architecture. They understand databases (when to use PostgreSQL vs. MongoDB), know how APIs should behave, understand deployment considerations, and can troubleshoot issues end-to-end. They don't operate in silos.
Communicative & Collaborative—exceptional developers explain technical decisions in terms non-technical stakeholders understand. They proactively flag risks, share progress transparently, and work well with designers, product managers, and other engineers. Remote work requires discipline—they respect async communication patterns and time zone differences.
Results-Oriented—they focus on shipping. While they care about code quality, they balance perfectionism with pragmatism. They can scope work realistically, deliver incremental value, and iterate based on feedback. They understand that "done and deployed" beats "perfect but never shipped."
Project Types Your Python Developers Handle
Web Applications & SaaS Platforms Building scalable, user-facing web applications. Whether it's a customer-facing portal, internal dashboard, or multi-tenant SaaS platform, Python developers create responsive, production-grade experiences. Common frameworks: Django, FastAPI, Flask.
Real scenarios: Building a customer portal with real-time notifications, scaling a Django app to handle 10x traffic, creating a new MVP in weeks, implementing complex business logic in REST APIs.
Backend APIs & Microservices Designing and building robust APIs that power your applications. Python developers create RESTful APIs, GraphQL endpoints, and event-driven architectures that handle millions of requests reliably.
Real scenarios: Designing a payment processing API, building a notification service, creating a real-time data API for mobile apps, extracting microservices from monoliths.
Data Engineering & Analytics Pipelines Building systems that transform raw data into business intelligence. Python developers design ETL pipelines, data warehouses, and analytics workflows that process everything from daily transaction logs to real-time streaming data.
Real scenarios: Setting up a data pipeline consolidating 10+ sources, building a recommendation engine, creating dashboards for business analytics.
AI & Machine Learning Solutions From model training to production deployment. Python developers build machine learning systems—whether that's computer vision for image recognition, NLP for text analysis, or predictive models for forecasting.
Real scenarios: Integrating an LLM into your product, building a recommendation system, creating an automated quality control system with computer vision.
DevOps & Infrastructure Automation Automating deployment, monitoring, and infrastructure management. Python developers build CI/CD pipelines, infrastructure-as-code solutions, and automation scripts that reduce manual toil.
Real scenarios: Setting up automated testing and deployment, containerizing an application, building monitoring and alerting systems.
Legacy System Modernization Breathing new life into existing codebases. Python developers refactor outdated systems, introduce modern practices (testing, CI/CD), and gradually migrate to scalable architectures.
Real scenarios: Migrating from Python 2 to Python 3, extracting services from a monolith, introducing automated testing to legacy code.
Rapid Prototyping & MVP Development Getting ideas validated quickly. Python's speed makes it ideal for building prototypes and minimum viable products that prove concepts before scaling investment.
Real scenarios: Building a proof-of-concept for a new product idea, rapid iteration based on user feedback, validating a business model with code.
Automation & Scripting Building systems to automate repetitive tasks. Python excels at scripts for data processing, system administration, and workflow automation.
Real scenarios: Automating daily data exports, building deployment scripts, creating monitoring automation.

Interview Questions for Python Developers

Question 1: "Walk me through how you'd architecture a scalable Python application from the ground up. What frameworks would you choose, how would you structure the code, and what decisions would you make about databases, caching, and deployment?"
Why this matters: Tests architectural thinking, framework expertise, and ability to make trade-off decisions. Reveals whether they design for scale from the start or solve problems reactively. Shows understanding of performance, maintainability, and team collaboration.
Question 2: "Tell me about a Python project where you had to optimize performance or tackle a scaling challenge. What was the bottleneck, how did you diagnose it, and what was the result?"
Why this matters: Tests real-world optimization experience and systematic debugging methodology. Reveals whether they understand Python performance characteristics, use profiling tools, and focus on actual bottlenecks versus premature optimization. Shows practical performance tuning skills.
Question 3: "Describe a complex feature or system you built in Python. How did you manage code organization and ensure it remained maintainable as complexity grew?"
Why this matters: Tests ability to manage complexity without letting shortcuts become technical debt. Reveals whether they write clean code from the start, use appropriate design patterns, and think about long-term maintainability. Shows maturity in handling larger Python projects.