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Python Developer Roles and Responsibilities

Before that, let us loosely glance through the following stats.

  • According to Statista’s research, in the year 2019, nearly 42% of developers worldwide use Python
  • As per TIOBE Index, Python leads as the most frequently taught language in the universities
  • Python dominates other programming languages on Google tutorial searches, accounting for 26% of the total tutorial search results
  • Python is the fastest-growing major programming language based on Stack Overflow traffic

Thus, as shown above, Python is one of the most versatile and fastest-growing programming languages.

To make you better understand the roles and responsibilities of a Python Developer, we have divided the entire blog into six main sections, which further boil down to a few baby steps and other structural carry-outs.

What is Python?

Python is an object-oriented, versatile, high-level programming language with dynamic semantics for web and application development. Its unique syntax and modular style design make learning stress-free. As a developer, you can read and translate Python code more easily than other languages. In addition, Python enables you to reuse and extend code in other projects.

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What can you do with Python? What is Python used for?

No other programming language is as generic as Python. The language is used for web development, Internet of Things (IoT), data analysis, Machine Learning (ML), etc.

What are the reasons?

  • Clear syntax
  • Abundant libraries
  • Faster ‘time to market’

Python is Google’s official server-side language. The world’s largest Django framework, which is Instagram BTW, is written in Python.

If you want a comprehensive insight into Python’s applicability and usage, go through this Python Tutorial video!

What is a Python Developer? What does a Python Developer do?

A Python Developer writes server-side web applications when working as a Web Developer. They also develop various back-end components to connect the web application to web services and more. Basically, a Python Developer develops, deploys, and debugs python projects.

How to become a Python Developer?

Like any other programming language, you need to do two things. The first is to learn and the second is to execute your learning.

If you are anticipating becoming a full-fledged Python Developer, take a few baby steps first. Go through our Python for beginners tutorial. Although it will definitely help you start, you must enroll yourself in an industry-recognized Python course.

If you want a comprehensive insight into the steps that you must take to learn Python, then you must read this blog on How to Become a Python Developer?

Python Developer Salary

Before treading further and explaining Python Developer roles and responsibilities, let us loosely glance through the average salary of a Python Programmer working in different profiles.

Python Developer Salary

Now, after you have gained substantial knowledge on ‘What is a Python Developer?,’ ‘What does a Python Developer do?,’ how to become a Python Developer, Python Developer salary, and whatnot, let us finally focus on Python Developer roles and responsibilities.

Although, if you want a quick glimpse of the Python Developer career path, here is an interesting blog that will help you decode How to build a career as a Python Developer?

Python Developer Roles and Responsibilities

A typical Python Developer codes, designs, and deploys applications. Furthermore, the person often has to debug codes, create integrable systems, etc. Although these may be true, a Python Developer’s roles and responsibilities depend on the job profile, industry or vertical, and work experience. Therefore, let us elucidate the roles and responsibilities by different categories. Here is a Python Developer’s roles and responsibilities based on the job profile:

Python Developer Roles

Python Web Developer

  • Write server-side logic
  • Work on web frameworks
  • Collaborate with the design team to gather end-users’ requirements
  • Develop the server-side platform
  • Deploy applications
  • Perform tuning, usability, improvement, and automation
  • Write reusable codes, etc.

Average Salary: US$118,124/year

Software Engineer

  • Develop and maintain software
  • Write and test codes
  • Integrate applications with third-party services
  • Debug programs
  • Implement security solutions
  • Enhance applications’ functionality
  • Assess feature modification requests
  • Provide technical solutions
  • Coordinate with internal teams, and more

Average Salary: US$110,021/year

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Automation Testing Engineer

  • Work on Python test framework tools, including Pytest, PyUnit, Behave, etc.
  • Perform complex system tests
  • Troubleshoot code issues
  • Create test scripts
  • Design the automation framework
  • Perform A/B testing
  • Coordinate with the development team, etc.

Average Salary: US$61,991–100,748/year

Data Analyst

  • Work on Python libraries, including Matplotlib, NumPy, Pandas, etc.
  • Carry out data analysis (interpretation)
  • Collate/collect data using the scripting language
  • Explore datasets
  • Interface with customers
  • Gather requirements
  • Tune applications or conduct query performance
  • Model data to assist reporting (ad-hoc or pre-defined)
  • Analyze problems
  • Communicate findings with the team or stakeholders
  • Perform A/B testing

Average Salary: US$62,237/year (entry-level)

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Data Scientist

  • Analyze data
  • Create predictive models for Machine Learning (ML)
  • Communicate and propose solutions to business challenges
  • Develop statistical learning models
  • Work with product management and technology teams to understand business needs and find possible solutions
  • Keep up with the most recent technology trends

Average Salary: US$121,762/year

Machine Learning Engineer

  • Perform statistical analysis of data
  • Put Machine Learning (ML) models into production
  • Research and transform Data Science prototypes
  • Research and implement appropriate ML algorithms and tools
  • Design the ML system
  • Develop ML applications
  • Perform ML tests
  • Fine-tune algorithms based on test results
  • Train and adapt the ML system as needed
  • Extend existing ML libraries
  • Keep up to date with the latest ML trends

Average Salary: US$138,601/year

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Python Developer Jobs

In the United States, Python Developers have nearly 25,000 job openings. This is a list of the current number of job opportunities for Python Developers based on their experience level.

  • Entry-level Python Developer Jobs: 4,834
  • Mid-level Python Developer Jobs: 14,396
  • Senior-level Python Developer Jobs: 5,498
Python Developer Jobs

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Python Engineer: Must-have Skills

For Python Engineers, here is a list of the must-have skills:

  • Core Python
  • Object-relation mappers
  • Multi-purpose architecture
  • Web frameworks
  • Code packaging, release, and deployment
  • Design skills
  • RESTful APIs
  • Scriptwriting
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How to take your Python skills to the next level?

If you have acquired all the necessary Python Developer roles and responsibilities and still feel that your Python knowledge is not up to the mark, then you need to move to the advanced level. To enumerate, let’s assume, you get the opportunity to work with a Data Scientist. In such a case, you will encounter ample occasions where you might feel that you just scratched the surface. Mind you, we are just talking about the intermediate or mid-level Python Developers. Anyhow, if you have such a feeling or notion, then you should rather be glad. It is important to realize that, along with assuming the roles and responsibilities, you have to learn new technologies and tools to make a transition.

Now, what areas can you tread into?

Well, you can opt for a role in DevOps or become a Data Scientist—if this excites you. Your Python knowledge can also lead you to have a successful career in Artificial Intelligence—given, you upskill your understanding of algorithms, analytics, and statistics. Now, to take your Python skills to the next level, you can enroll in our Data Science with Python. This will help you leverage your skills in the Data Science domain.

Go through these Advanced Python Interview Questions to crack your interviews.

The Curious Case of NASA

As Data Science, Big Data, and Machine Learning are growing exponentially, companies around the world prefer Python over other programming languages to use in these emerging technologies. To emphasize this, let’s take NASA as an example.

First, let’s take a look at some of the issues NASA faced before using Python.

  • Data processing problem
  • Data exchange problem
  • Issues with tracking the data changes
  • Errors in workflow management

All these aforementioned issues could have been solved by C++ or Java, but the NASA programmers were in search of a language that could bring reliable results, with less money and lesser baggage.

Out-of-the-box solutions provided by Python:

  • Dynamic typing
  • Python interpreter
  • Pseudo syntax
  • Easy to maintain
  • Simple user interface

Because Python is very easy to learn, most programmers and some non-programmers became proficient in the language. As a result, many NASA-scheduled Space Shuttle missions use Python as their core programming language.

More and more companies are looking for roles that rely heavily on Python and as you suspect, these roles are also among the most rewarding job roles. Furthermore, the jobs that require Python as a skill have also increased dramatically in recent years. Many latest research data show that Python programming skills are the highest paid among others. In addition, a Python certification can easily help you with Python jobs compared to other programming languages ​​such as R, Scala, and Java.

Intellipaat has an exceptional Online Python Certification Program to help learners expand their understanding of the Python language. All the way through the course, we offer real-time interactive sessions conducted by leading Python experts. When you sign up for the course, you will learn the most important aspects of Python, including various Python tools, Hadoop, Machine Learning, and more.

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