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Introduction
Hello Ninjas!
Do you know we produce ten times more data every year than the previous year? And to manage this huge rise in data, Data engineers come into the picture. Around 15 lakhs engineering graduates graduate every year we still have a shortage of data engineers.
So let's get familiar with the role of data engineers at Lenskart.
In this blog, we will discuss the role of data engineers at Lenskart, how to become a data engineer at Lenskart, the perks, job responsibilities, career map, etc., of data engineers at Lenskart.
About Lenskart
Lenskart is a Leading e-commerce portal for Eyewear based in New Delhi, India. It was founded by Peyush Bansal in 2010 with a vision to provide high-quality Eyewear.
The aim of Peyush Bansal is to spread awareness of eye-checkup among all people, including all small households, where women come close to the television to watch the program. They are now aiming to provide the best eyewear, along with checkups too, all over India. Moreover, planning to expand over the other countries to help people there too.
Salary and Perks
The average salary for a mid-career Data Engineer at Lenskart is shown in the table below.
**The salaries mentioned above are only estimates. The actual salary may vary.**
Perks of the Role
Below are the few benefits that you receive as a Data Engineer at Lenskart.
Free food and transport, depending on the project.
Health insurance
Team outings
Child care
Incentives based on work efficiency
International Relocation
**The benefits offered are based on your position in the company and work efficiency**
Skills and Experience Required
In this section, we will cover the skills and experience required for this job role.
Eligibility
The eligibility criteria for becoming Data Engineer at Lenskart are as follows:
BE/B.Tech/BCA/MCA/M.Sc./MS/MTech/ME with at least three years of relevant experience post-qualification.
B.Sc. Graduates with at least 3+ years of relevant experience post qualification.
Working with and supporting cross-functional teams.
Other Skills
Nowadays, getting a job is equivalent to winning a competition. But having only technical skills is not only efficient, so peers should also work on their non-technical skills. One can stand out through non-technical. A few skills that will create a unique impression of you are:
Below are the responsibilities that you will be in charge of:
Build And optimize big data, data pipelines, architectures, and data sets.
Perform analysis of both internal and external data.
Address business questions with specific answers.
Take charge of the tasks assigned.
Analyze the data sets carefully and efficiently.
Extract, manipulate and process extensive discrete data.
Improve and enhance the current data format.
Have to manage projects along with the organization.
Career Map
People only see themselves at a more satisfactory place or level after acquiring skills and experiences. A data engineer comes best after doing many company projects or leading a team.
The more you indulge in discussions, technical events, and projects, the more you get skilled and fruitful for your future companies of which you can be a part.
The designation or level of the future jobs also depends on your verbal and non-technical skills, so it's equally important to balance and develop both non-technical ad technical skills.
Different Job Levels at Lenskart
So below are some levels of Data engineering at Lenskart:
Initially, as a fresher, you will join as a software engineer or business analyst. Dealing with data ELT(extract, transform, and load) as a Data Engineer at Lenskart is not an entry-level job.
As you gain experience and skills, you move up to the Data engineer-I role at Lenskart. This is the level that you join as a data engineer at Lenskart.
As a Manager, you will design data systems based on ELT while guiding the team under your leadership.
The senior manager deals with issues that arise with people under him. He also works on presenting ideas to respective seniors.
*Rest also depends on how you perform in the company in your current job position*.
Preparation Strategy
Let us now cover the strategy for our preparations:
📑 Join a good course for programming
This will make you understand the basic concepts of everything that you need to know and learn. A course is suggested because your learning pace is systematically divided into parts and durations.
Choose a course that includes languages like SQL, NoSQL, Python, JAVA, R, Big Data, etc.
📑 Gain Mastership
Whichever course you take, make sure to complete it and master it. Taking a course is easy, but completing it and mastering it is difficult, which most students fail to do; so many people lag in this area, so you should make sure to solve a number of problems on each topic from the course to make yourself stronger in each topic.
📑 Machine learning And Python
Today in the data analyst or data engineer role, the most important language that is being used is machine learning and Python, so it's important to learn them and have a command over them; you should not be an expert in them, but you can try to have a decent level of problem-solving and problem analyzing in this field.
While machine learning is more the concern of data scientists, it can be helpful to have a grasp of the basic concepts to better understand the needs of data scientists on your team.
📑 Do Projects
After you have completed a course or a particular book, you can start practicing problems, or you can directly start to build projects; you may start with small projects and learn basics from them, and afterward, you can increase the level of projects accordingly.
Doing projects helps a lot in understanding the real problems that occur and also develops our skills to solve those problems, which is a very important part of any role.
📑 Try to Learn the Maximum From Projects.
After completing a project, Students feel that they have made up a huge project, and they feel that they know everything, which is not true. While doing a project, you should be able to understand how things are done and how we are implementing code to do a particular task.
It is believed that the major learning of a particular topic comes after you've done a project obediently. You might have heard that seniors usually advise doing a project, but here the quantity never matters, but the quality of a project will take you forward.
So do projects and focus on learning maximum concepts from projects; this increases your practical skills and what exactly the company requires.
📑 Create a portfolio. Work on good cases and add them to your portfolio.
The portfolio is also called a CV (curriculum vitae). It consists of all the information regarding you, from your name, education, experience, certificates, extracurricular activities, etc. It is basically everything you want the employer to know about you. If you have worked on any project or case, don't forget to add that to your portfolio. It will make you stand out from other candidates.
📑 Actively look for data engineer job openings at Lenskart.
Now that you have learned all the required skills and worked on cases to gain practical knowledge and your portfolio prepared, you can now apply for the job of a data engineer at Lenskart. All the luck to you! Keep practicing, ninjas.
You can use the Coding Ninjas interview preparation resource
Prepare and Practice for a Technical Mock Interviews With Coding Ninjas.
Frequently Asked Questions
What questions are asked in Data Engineer at Lenskart interview?
Some questions asked in a Data Engineer at Lenskart interview are: Define Data Engineering, What is Data Modelling, List various types of design schemas in Data Modelling, and Distinguish between structured and unstructured data.
What is the role of a data engineer?
Peers are asked to visualize data or do an analysis of data sets. They build data to concatenate all information.
Does the data engineer do coding?
Well, yes, you need to be strong in coding. Along with experience or practical knowledge of the data sets, data pipelines, and analysis.
How to Prepare for the Data Engineer at Lenskart Interview?
To be a Data Engineer at Lenskart, do coding consistently, practice SQL commands, do projects on it, practice analyzing data sets, and visualization of data internally and externally.
Is the data engineer job stressful?
No, we cannot conclude with a particular answer, but yes, you will have stress if you don't do your tasks regularly; otherwise, it's pretty awesome to work as Data Engineer at Lenskart.
Conclusion
We have learned what data engineering is and how to become a data engineer at Lenskart. We have also discussed the various responsibilities, benefits, and requirements, along with the career map of a data engineer at Lenskart.
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