Python is a general-purpose programming language used for both web development and big data processing. It steadily occupies a prominent niche in the fields of data engineering and data science. Python has a low entry barrier as its syntax is straightforward and concise, making it appealing to new programmers. Python developer interviews are held by the team within two specialties: and . In this article, Alexey Novikov, Team Lead of the Python Department, and Evgenia Bogomaz, Group Lead of the Python Department, discuss what will help you pass the interview for a Python developer position. We’ll pass it to them. NIX United web data engineering First and foremost: what we look for in a resume Junior The key points of a resume we are interested in depend on which position the applicant is applying for. It stands to reason that a junior specialist wouldn’t have a long track record of working on a variety of intriguing and challenging tasks. Therefore, we pay more in novice developers’ CVs, whether he or she is studying now, and if so, what year he or she is in. attention to the education Often, first-year students come to us, and not all of them can envision how they will balance studying with working on a project. For our part, we provide the option to take a study break during exam weeks, and we also attempt to create a flexible timetable so that the newcomer has enough time to study at his or her university and dedicate time to IT projects. It’s also vital to determine from a junior candidate’s resume what expertise and resources he or she holds before training. If there are any runtimes in CVS (GitHub, GitLab, etc.), we inspect the code and, during the interview, ask the applicant why he or she adopted a certain technique. Don't be too hesitant to include a few personal words about yourself in your CV. Knowing a person's aims and aspirations, as well as his or her hobbies, is quite beneficial. After all, we understand that the first few months of a junior position consist of active skill development, which necessitates frequent communication.  It’s impossible to build effective communication without getting to know the person. Middle/Senior For this position, we have other priorities. We should , understand areas in which he or she has worked, as well as technology used and responsibilities held. In this scenario, we also consider how many jobs the applicant has had over a period of time. ensure that the person in front of us is an experienced specialist Exaggeratedly, "five firms in a year and a half" may already be a red flag that the candidate won’t be able to establish a foothold with us. Then we check to see if the candidate is currently employed or has recently left a previous project. If the candidate completes the interview successfully, we will know when to expect him or her to join us. During the interview, we focus on specific technologies as well as decision-making experience, application architecture development experience, and soft skills. and thus need to be able to effectively build team communication, explain goals and objectives accurately, resolve conflicts, and be ready to teach newcomers. Professionals at this level frequently stand as a project's lead role I'd like to call attention to those who come to us for freelance work. For them, the most important reason is to get experience engaging with other team members, and as a result, they are able to grow as specialists. Typically, freelancers’ code is not often evaluated, and they have no one to consult or receive feedback from. However, if you’re new to our team, a mentor will always assist you, and more experienced developers will share their knowledge and offer advice on how to tackle new problems. We also appreciate seeing seasoned pros as everyone can bring their own unique experience and perspective to projects—this is how we learn from each other. What does theory teach us? A Python developer position, like any other backend programming language, assumes: Confident knowledge of the language Comprehension of client-server architecture Familiarity with the HTTP protocol Ability to work with a version control system SQL expertise Knowledge of database design principles At the interview, our goal is , what they already know and can apply to the project right away, as well as what they need to learn. We understand that you will never be able to know everything. not to fail the person but to help them understand Furthermore, candidates are frequently apprehensive during interviews and may forget something important. This is something we are aware of. Therefore, the most important thing for us is to see how the person thinks. We also without creating code, by simply talking through the solution strategy. In these exercises, there are frequently multiple possibilities, and we are always curious to see which one the candidate chooses. At this point, it’s usually clear how well the candidate knows the base points to solving problems. These are our unique signature tasks, which you won't find anywhere online. present cases that can be solved verbally, What job seekers typically overlook while preparing for a job interview Many are interested in the and Data Scientist professions, which employ Python to process big data and machine learning. Data Engineer Being a specialist in this field is swag, yet applicants often have no understanding of what they'll be dealing with or what basic technology stack they'll need. Our advice: don’t be lazy, and read in advance about the position for which you apply. One of the most prevalent subjects that new Python developers are unfamiliar with is . Many concentrate on database syntax and queries when preparing for interviews; however, while speaking with applicants, it becomes clear that they don't completely comprehend to develop an effective data warehouse, nor how to . relational database architecture what tables are required link them or implement restrictions We frequently meet people who have only used ORM to deal with databases. , , and in our line of work, the ability to properly build a database is critical. However, for real-world projects requiring complicated queries and database optimization this knowledge is frequently insufficient It’s not a crime to lack certain knowledge We don't have a magic question that tells us whether to reject a candidate or invite him back for a second interview right away. Our process helps us assess how much the applicant has demonstrated, how he/she views his/her own professional development in the future, and whether he/she is ready to work with us. Following the interview, everyone receives feedback (at the end of the conversation or a few days later). We strive to give credit for what we've accomplished while also highlighting areas that need to be improved. Occasionally, the preparation after these second chances exceeds our expectations. A candidate for a Data Engineer position, for example, came to us once. He didn't have enough knowledge at the time of the first interview, so we advised him to study and return better prepared. We shared with him self-study resources developed by our professionals for such situations, as we do with all candidates, and we sent him home. We frequently grant second chances. The candidate returned to us and proved his worth but for a different position as a web developer. He has now completed the server portion of one of the applications and intends to become a full-stack developer. As you can see, there exist various scenarios and outcomes for our applicants. As experience has shown, the technical component of talents is not always the most important. The applicant's potential, whether seen or unseen, plays a critical role. If a candidate can think logically and discover the best answer to a problem, and if he has an analytical mind, he or she will have a major advantage over other applicants. This is true even if the applicant lacks a thorough understanding of technology. Learning to think technically comes with experience, but training someone to think logically and rationally is considerably more difficult. Finally, some justifications for studying Python Python is a beginner-friendly programming language that is very simple to learn for more experienced programmers. It will be extremely useful if you want to work on the backend or want to pursue a career in big data. With Python, each of your projects will be unique. Each one has its own set of challenges and tricks that you may overcome with off-the-shelf or custom solutions. Are you interested in learning the fundamentals of Python theory? To assist you in preparing for your interview, we've put together some helpful resources below. Take advantage of these and check them out! Links to useful resources on Python and its ecosystem Books - The Python Developer's “Bible". Readable at all levels of Python learning; - a fantastic small book about the many Python tricks; - in simple terms, this is a book about algorithms using Python examples; - the book covers the fundamentals of working with Django Admin; - an e-book with examples. Mark Lutz “Learning Python” Python Tricks: The Book Grokking Algorithms Django Admin Cookbook Django Book Courses - MIT course; - the course for everybody from the University of Michigan; - simple and offered by Google. Introduction to Computer Science and Programming Using Python Python for Everybody Specialization Crush Course on Python Interesting reading - many useful tutorials; - learn about Python's finest framework. Real Python Django: The Web framework for perfectionists with deadlines Digest Python Hub Database-related hyperlinks - don't let the book's length deter you; it contains both theory and practice on databases; Notes for Professionals book covers almost all major operations; Notes for Professionals book using Postgres as an example for understanding relational databases. An Introduction to Database Systems by C.J. Date MySQL. PostgreSQL. Online Tutorial SQL Tutorial GIT+LINUX - you don't need anything else but practice; Pro Git A brief introduction to Apache Spark We recommend getting to know Apache Spark, one of the most popular tools for big data processing and analysis, if you wish to learn not just the foundations of Python but also delve deep into big data & data engineering. Official Documentation There's no better place to learn about Spark's basic components, what distributed computing is, what data structures it uses, and the meanings of terms like Lazy Evaluation, Fault Tolerance, Catalyst Optimizer, UDF, Transformations, Actions, Wide & Narrow Operations, Partitions, Shuffle, Broadcast, and more than the official documentation: https://spark.apache.org/; https://spark.apache.org/docs/latest/quick-start.html; https://spark.apache.org/docs/latest/api/python/ Books - it's an excellent place to start learning about such a fascinating topic as Big Data; - for massive data processing and analysis, Apache Spark has become the de-facto standard; - is a book about how to get the most out of Spark; - the Hadoop ecosystem is introduced as a crucial tool for storing and processing massive data in this book. Big Data Fundamentals: Concepts, Drivers & Techniques Learning Spark: Lightning-Fast Data Analytics High-Performance Spark Hadoop: The Definitive Guide Courses and videos - Apache Spark's primary contributor; - Edureka's PySpark course. Databricks PySpark Tutorial for Beginners Interesting reading ; Big Data Zone Medium selection; Data Engineering Podcast.

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