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Table of contents
1.
Introduction🌼
2.
About the Job👩🏻‍💻
3.
Salary💸💸
4.
Benefits and Perks
5.
Eligibility Criteria🧑‍🎓
6.
Roles and Responsibilities of Data Engineer🤝
7.
Roadmap and Career map for the job🛣️
8.
Preparation Tips and Resources
9.
Frequently Asked Questions
9.1.
Who is Data Engineer?
9.2.
Is getting a job at Apple hard?
9.3.
What degree do I need to work at Apple?
9.4.
Are Apple Interviews hard?
9.5.
How many interviews does Apple do?
10.
Conclusion
Last Updated: Mar 27, 2024

Data Engineer at Apple

Author Shiva
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Introduction🌼

So, have you already made up your mind to work for Apple as a data engineer? Hi Ninja, You are in the proper location.

Employers from all over the world are looking for qualified individuals to help them organize their data sets into information that will enable them to grow their customer base. As a result, this specialist field was created. In this blog, we'll make sure you know everything there is to know about Apple's specialist profession of data engineers.

introductory image

Apple is a global American IT corporation with headquarters in Cupertino, California that focuses on software, internet services, and consumer devices. Here, we'll provide you with a detailed road map to achieving your ideal position.

So let's begin: Apple has a team of varied thinkers and doers continuously reimagining what is possible to help us all achieve the things we love in innovative ways.

Further reinforcing our resolve to leave the world in better shape than we found, it is the innovation that goes into the company's products and how they conduct business. This is where you may see how your efforts affect both your own life and the lives of other people.

Interested in working as a data engineer at Apple? Relax; Coding Ninja is here to help you at every turn.

About the Job👩🏻‍💻

Data scientists and business analysts can use the information created by data engineers' systems to assess unprocessed data in a variety of scenarios. Their ultimate goal is to make data accessible so that companies may use it to evaluate and enhance their performance.

job image

Apple, an Equal Opportunity Employer, is committed to diversity and inclusion. They use affirmative action to give all applicants, including women, protected veterans, minorities, and individuals with disabilities, opportunities for employment and professional advancement.

To make sure you are on the proper path, it is time to talk about the eligibility requirements.

 

Salary💸💸

The salary for the Data Engineer at Apple for a fresher(Year of experience: 4 to 11 years) is:


salary image

Years of Experience

Average Salary

~ 3 - 4

₹18 LPA

~ 4 - 5

₹21 LPA

~ 7 - 8

₹22 LPA

~ 9 - 10

₹27 LPA

~ 10 - 11

₹31 LPA

 

For workers with experience ranging from three to ten years, the average annual salary for Apple Data Engineers in India is ₹ 25 Lakhs. The annual compensation range for a Data Engineer at Apple is between ₹ 17 and ₹ 35 lakhs.

** The figures presented above are subject to change.

Benefits and Perks

High moral and ethical standards, a healthy corporate culture, and favorable working circumstances are all characteristics of the well-known corporation Apple. The squad captain and players are open and incredibly helpful. Some advantages of working at Apple include-

🏡 Work From Home

🩺 Health Insurance

💸 Savings and investments

🎗️ Giving programs

🛎️ Cafeteria

🤸 Gymnasium

🏖️ Team Outings

👨‍🏫 Soft Skill Training

📚 Job Training

🚉 Free Transport

🍔 Free Food

👪 Maternity and paternity leave

🧑🏼‍🤝‍🧑🏽Opportunities to network and connect

✈️ International Relocation

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Eligibility Criteria🧑‍🎓

Employers at Apple look for an individual having at least a bachelor's degree in computer science, engineering, mathematics, or information technology to get the job of a Data Engineer at Apple. 


Eligibility image

An applicant must meet the following requirements in order to be considered for the role of Data Engineer at Apple:
 

  • Working knowledge of relational and non-relational databases, data warehouses, data marts, data models, ETL/ELT, reporting, and analytical tools.
     
  • Knowledge of at least one programming language and experience designing applications, data pipelines, and analytics solutions (Python, Java)
     
  • Have experience creating SQL queries and tweaking performance 
     
  • Have a thorough understanding of agile approaches and development processes
     
  • The ability to communicate complicated technical issues to business users who are not technically savvy as well as strong analytical and communication abilities.
     
  • Self-motivated, highly motivated, and able to pick things up quickly. • Exposure to reporting tools like SAP BO, Tableau, etc.

 

Now that you think you are eligible for the company let’s discuss the roles and responsibilities of this job role.

Roles and Responsibilities of Data Engineer🤝

The main responsibilities of this position are to:

roles and responsiblities image

  • Make use of tools and technology from the newest generation, and create highly scalable data pipelines.
     
  • Develop scalable technical solutions that adhere to data warehousing design standards for complex business needs.
     
  • Strong awareness of the demands for analytics and initiative to design generic solutions to increase efficiency.
     
  • Create analytical and reporting tools that offer actionable insights to support corporate activities.
     
  • Identify and automate manual data delivery procedures in close collaboration with business intelligence and machine learning engineers.
     
  • Good business sales knowledge, spanning both the consumer and business industries. Business process knowledge in the areas of operations and finance is a plus.

Roadmap and Career map for the job🛣️

Now that you are well aware of the perks Apple provides and the impact it will have on your life, I am confident you want to join Apple. 

roadmap image

But how do you go about doing that? How much practice is sufficient? What are the topics you must practice? What happens in Apple interviews? In Apple interviews, what types of questions are asked? Are you a good fit for Apple?

 

  1. Creating a Base (SQL, Coding, Linux): You need a strong foundation before diving deeply into data engineering specifics. Learning some of the more advanced ideas and techniques related to distributed computing or streaming can be alluring. But doing so would be like to studying letters before words and sentences. You should therefore start with SQL, programming, and some server/Linux fundamentals. These three abilities will help you comprehend how to communicate with computers from multiple layers and will enable you to speak to computers in their language.
     
  2. Building A Flask API Should Be Your First Project: Working with APIs is a constant requirement if you want to become a data engineer. either to automate processes or pull data. A great initial project is creating an API because it requires you to use a variety of technological levels. The terms ports, HTTP requests, coding, command line, and, if you really want to spice things up, maybe even play around with the cloud by establishing a VM to power your API, are all things you'll need to be familiar with. But that's a very lofty goal. Start off easy. You may quickly develop an API with Flask, a fantastic Python utility. I won't, however, presume that you are familiar with how to build your first API.
     
  3. Learn Testing: It's possible that you never even studied testing in school, or perhaps you took a single course testing briefly in one unit over the course of one week. Nowadays, testing is a standard aspect of the CI/CD process and QA engineers are few and hard to come by. You are able to create test cases. You must understand the distinction between integration tests and unit tests.
     
  4. Learn about Data Pipelines: The skill sets of data engineers, software engineers, and data scientists. All three frequently use Python, both data scientists and data engineers frequently use SQL, and all three depend to some extent on a working knowledge of Linux. So what makes data engineers unique? The emphasis on data pipelines and warehouses is among the key differentiators. Data engineers must comprehend the principles of data warehouses and data pipelines. They are the foundation of any successful DE.
     
  5. NoSQL Databases and Cloud: You have probably already experimented with the Cloud a little and perhaps even used a NoSQL database. But let's complete that information. How? Well, when it comes to completing information, there are a few excellent possibilities. For instance, I believe that right now would be a wonderful time to enroll in a certificate program.
     
  6. Distributed System and Streaming: In the modern world, there are numerous methods for processing data. More significantly, it's now much simpler than ever to use more complicated systems, such as streaming or distributed systems. You may get started by spinning up a fully managed service on AWS or GCP. There's no need to launch five more services solely to manage and organize your streaming setup.
     

Seniority, impact, and scope of responsibilities determine Apple's job levels. Each level is assigned a salary band and a job title, and advancement necessitates the acquisition of a specific set of qualifications, skills, and experience. Apple's clear job hierarchies help maximize career advancement opportunities, improve internal mobility, and promote transparent company culture.
 

  1. Chief Data Officer: This executive-level position oversees data governance, develops strategy, and takes a more active part in analysis and business intelligence. It also assumes accountability for data across the entire organization. The objective of this function, which is more business-focused, is to match data with corporate strategy.
     
  2. Manager of Data Engineering: Many senior-level engineers go into a more managerial position, managing the data engineering division of a corporation. This position combines managerial and development aspects. A group of data engineers is led by managers, who also assist with coaching, vetting, and driving the department's goal. The expansion of the data engineering team is another priority for managers, who also actively participate in hiring, mentoring, and performance evaluation.
     
  3. Data Architect: Data engineers and data architects collaborate closely. In essence, the data architect gives the engineering division the blueprint, which serves as a guide for developing sophisticated data models and pipelines. This position is focused on business: Data architects assist in creating pipelines that are tailored to particular requirements and have a solid understanding of the direction and strategy of the organization.
     
  4. Data Science Engineer: The data science engineer is a hybrid position that is sometimes referred to as a full-stack data scientist. A full-stack data scientist creates and maintains pipelines and guarantees that the model can produce useful business insights.

Preparation Tips and Resources

To prepare, we must have a collection of good resources. As for Data Engineer at Apple, 

To prepare for these interview rounds, here we have a few more resources for you:
 

preparation image

Also, prepare yourself with attractive answers to the below-mentioned questions:

  • The time you disagree with the team and how you dealt with that.
     
  • Explain a situation when you were leading a group.
     
  • In a situation where your client has unreasonable demands, how do you respond to them?
     
  • Where you take a leadership role formally or informally.
     
  • The time you were at risk for any particular challenging project. 
     

While giving your interview, just be relaxed and give answers calmly and confidently.

We wish you all the very best.🤗

Frequently Asked Questions

Who is Data Engineer?

A data engineer is an IT specialist whose primary duty is to prepare data for analytical or operational use. The task of building data pipelines to aggregate data from numerous source systems frequently falls to these software engineers.

Is getting a job at Apple hard?

Getting a job at Apple may be quite difficult, as is the case with many of these digital behemoths. In fact, because Apple has so many stringent and demanding conditions you must satisfy to become a full-time associate, getting a full-time position is frequently touted as being impossible.

What degree do I need to work at Apple?

Students who major in computer science should be well-versed in software, cybersecurity, and engineering. There are so many sides to a business that a variety of majors are eligible to apply for jobs at Apple and other significant tech firms.

Are Apple Interviews hard?

Yes, Apple interviews are renowned for being challenging. Practice Interviews a lot before the actual interview.

How many interviews does Apple do?

You will be interviewed by two individuals at once, which is a novel approach used by Apple for in-person interviews. Several team leads are interviewed on-site over the course of six to eight rounds.

Conclusion

In this article, we thoroughly discussed the process to become a Data Engineer at Apple, what are the skill sets required, roadmaps, and important links that you can also refer to. I hope that this article has helped you to enhance your knowledge regarding the Data Engineer role and its interview preparation as well as process if you would like to learn more, check out our articles on  

Please refer to our guided paths on Coding Ninjas Studio to learn more about DSA, Competitive Programming, JavaScript, System Design, etc. And also, enroll in our courses and refer to the mock test and problems available. Have a look at the interview experiences and interview bundle for placement preparations.

 

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