The Python programming language is widely used by companies around the world to build web apps, analyze data, automate operations via DevOps and create reliable, scalable enterprise applications.
There is also a fantastic list of organizations using Python on the Python.org wiki as well as a detailed write-up of several top Python-powered companies on Real Python's blog.
Many companies do not even realize they are using Python across their organizations. For example, if a company is a "Java-only shop" but they use IBM WebSphere as a web application server then they have to use Python to script the server's configuration! Python has a habit of getting in everywhere regardless of whether the usage is intentional.
Python is widely-used across financial institutions, whether they are hedge funds, large banks or regulators (see "Government Agencies" section below).
Goldman Sachs uses Python and often asks candidates about their experience with the language during the interview process.
You can see publicly what companies are using internally by looking at job descriptions on sites like Glassdoor with "Python Goldman Sachs" keywords and Indeed for JP Morgan Chase. Salaries and responsibilities vary widely based on the role and whether Python is used for data analysis, web application development or DevOps.
PayPal uses Python across their entire infrastructure and often writes great technical blog posts on packaging, optimization using C and configuring DNS.
Large technology companies tend to be polyglot (use many programming languages rather than standardizing on one), with Python either as a primary language or the "glue" that helps all the other languages fit together. The following articles explain how these leading large companies like Uber, Twilio, Netflix and Facebook uses Python in their development stacks.
Uber's tech stack contains a significant amount of Python, which they documented in a series of engineering posts. Part one describes the lower backend levels, which are written in Python, with Node.js, Go and Java mixed in. Part two explains the higher levels of the marketplace and user interfaces.
Twilio uses Python with Django and the Wagtail content management system to power the amazing Twilio documentation as well as TwilioQuest. They wrote a post about how TwilioQuest was built that goes into detail on the code including the usage of the front-end Vue.js framework. Twilio also uses Flask to run the REST API endpoints and open sourced the Flask-RESTful framework so other developers could cut down the boilerplate in their web APIs.
Netflix uses Python throughout their organization to run chaos engineering tests and generally glue together the code from their high-functioning polyglot teams. Netflix also wrote a 2019 update for PyCon US to give more detail on what teams and projects work in Python.
Python 3 at Mozilla explains how their "build system, CI configuration, test harnesses, command line tooling and countless other scripts, tools or Github projects are all handled by Python". So just about everything a developer touches every day to build anything else needs Python to hook into the larger organization!
Google uses Python extensively and officially supports it internally as one of their three core languages, the other two being Java and Golang. While Google likely has every programming language running somewhere in their infrastructure, Python receives priority support due to its core language status.
Dropbox is well-known for using Python across their application development, infrastructure and operations. They also did a good job of cornering the market on hiring well-known Python core contributors for a period of time, such as Guido van Rossum and Jessica McKellar (although Jessica is now at a new company that she co-founded).
Facebook and Instagram use Python 3 at scale. They've been very vocal about successfully making the migration from the Python 2 world into Python 3.
A significant portion of Reddit is built in Python and it is one of the largest sites at scale to use the programming language.
Increment covers usage of Python (and other programming languages) at Lyft, Digital Ocean, Sauce Labs, Slack and Fastly in this awesome overview post titled "What its like to be a developer at...".
Python usage in government agencies is widespread despite the reputation of agencies as stodgy late technology adopters. Organizations range from financial industry regulators like the SEC and CFPB, to intelligence agencies like the CIA, FBI and NSA.
The Consumer Financial Protection Bureau (CFPB) not only uses Python for running most of their applications but also open sources many of those Python projects for other agencies (or any organization) to use. For example, collab is a Django project that provides an enterprise application for storing and looking up information on employees and contractors.
NASA uses Python extensively and open sources much of their software.
The United States Central Intelligence Agency (CIA) appears to be a huge fan of using Python in its state sponsored hacking tools. They even published their own Python code conventions documentation due to how many developers at the agency are using the language.
The SEC uses Python and proposes organizations use Python to comply with regulations.
A quick search for government jobs that require or recommend Python via USAJobs turns up numerous listings at organizations such as the Smithsonian Institution, Department of Education, Department of the Navy and National Institute of Standards and Technology (NIST).
Python is so widely used across various industries that developers have written guides specific to their occupations for how to use Python. The following resources are guides for using Python in astronomy, social sciences and other fields rather than specific companies.
Practical Business Python covers business-related topics such as how to automate generating large Excel spreadsheets or perform analysis when your data is locked in Microsoft Office files.
Practical Python for Astronomers gives open source workshop materials to teach astronomy students how to use Python for data analysis.
Python for the Humanities is a textbook on the basics of text processing in Python. The material ramps up quickly after the first chapter so you will likely want to combine this walkthrough with other great Python learning resources.
Python for Social Scientists and Real Python's Python for Social Scientists walkthroughs are specific to fields that work with a lot of data gathered from studies such as psychology, sociology and economics.