At Apple, the Data Engineering role is considered one of the most vital components of any analytics team. From creating critical, optimized pipelines to devising platforms that support customer analytics, data engineers do it all. These responsibilities require proficiency in various technologies such as SQL, Spark, Hadoop, as well as a good product sense and attention to detail.
Data engineers at Apple work alongside Data Analytics teams, Product Marketing teams, and various infrastructure and operations teams. Data engineers determine what data is collected and how it should be stored so that it can be accessed quickly.
Data engineering interviews at Apple usually filter for the following qualities -
- Experience in projects associated with software and data engineering.
- Good knowledge of Database Management and the ability to look for trends in data and analyze them.
- Proficiency in technologies such as SQL, Hadoop, MapReduce, Kubernetes, Spark, etc.
- Additionally, they must have the ability to design efficient databases, which are best suited to the functioning of the company.
The Apple Data Engineering interview consists of 4 rounds.
The first round is a telephonic interview with the HR. The HR schedules the next interview i.e. the Manager interview, which will primarily be a discussion about previous projects that you have worked on. The third round will be a Technical Phone interview where basic programming skills, SQL, and ETL will be tested. The final and most important is the onsite round, which consists of 4-5 interview rounds. You will be tested on Complex SQL, Database Design, Data Modeling, and Data Warehousing.
This is the first call from the company where you will be talking to the HR. You will be asked to briefly introduce yourself and talk about relevant projects you’ve done in your past roles. The HR will also schedule the next interview i.e., the interview with the Manager.
- Be prepared with projects that focus on your Data Engineering skills.
- While introducing yourself, talk about your skills and the qualities that you feel help you stand out strongly.
In this interview, you will be talking to the hiring manager. It will primarily focus on your project experience. They may also ask behavioral and technical questions based on past projects. The interviewer will assess what you have learnt while working on your projects.
- Be ready for the ‘Tell me about yourself’ starter.
- Be prepared to talk about your projects and highlight relevant skills and experience.
Behavioral questions such as the following may be asked -
- Tell me about a time when you couldn’t meet a deadline. What did you do?
- Describe a long-term project you managed. How did you ensure that you met all deadlines?
This is a 60-minute coding telephonic interview with a senior team member. Questions will revolve around -
- Basic programming in Java, Python, etc.
- Your past work, roles, and responsibilities.
- Technology associated with Data Engineering.
What the interviewer will assess
- The quality of the code/solution you will present and how much clarity you have while deriving it.
- Your command of SQL and how well you can handle the queries.
- Clarify all doubts before moving on to the coding part.
- Think out loud so that the interviewer understands your thought process. They might give you a hint or two. Make sure to consider them and either alter your approach or give the reason why you think your approach is better.
- The interviewer wants to see how good you are at problem-solving. It’s OK to ask questions on relatively trivial issues such as syntax.
- Why do you want to be a Data Engineer?
- What is your experience in working with SQL (or any other technology you will mention while discussing previous projects)?
- Are Parquet files better than CSV files? Explain.
- What are different types of memories in Java?
- What is the difference between Postgres and Redshift?
- What is the difference between Python and Scala?
- Write a function to print the data of a binary tree structure from left to right or from right to left according to input from the user.
- Compute the median of a given list. Optimize your code for long lists.
- Why do you think Spark is preferred over Mapreduce?
- What are the ‘pivot’ and ‘unpivot’ statements in SQL?
- Behavioral questions such as the following may be asked -
- You will be given a scenario and have to give your insights about how you will handle it.
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This is the final set of interviews and is considered the most challenging round. It will test your presence of mind and how efficiently you are able to react under pressure. The following interviews take place -
- Coding interview
- Data Design interview
- Interview with Hiring Manager
- Interview with a Senior Team Member (such as a Software Engineer, Data Engineer, etc.).
The topics tested during the interviews are -
- Complex SQL
- Database Design
- Data Modeling
- Data Warehousing
What the interviewer will assess
- Coding Round - Your general programming skills, technical concepts, and problem-solving approach will be tested. You will be expected to write code for the questions.
- Database Design interview - How well you understand the problem, derive data from it, and transform it into solutions.
- Interview with Hiring Manager - This will be a general discussion about the job and your role in the company.
- Interview with a Senior Team Member - Your coding skills will be put to test. The interviewer may delve deep into conceptual topics or ask you to work out the algorithms and codes for various questions.
- Practice scenario-based questions. This way you’ll get an idea about the type of questions that will be asked, and be more confident while answering them.
- Have a good command of SQL queries.
- Practice string manipulation questions such as -
- Questions based on experience may be asked, such as -
- Explain the concept of Monkey Patching with the help of an example.
- What is an aggregate function in SQL?
- What is a window function?
- Describe the physical and logical schema in SQL.
- Given an order table, do a market basket analysis on the order details.
- What is the importance of AWS Redshift and Spark? Explain their functions.
Note: Questions on basic programming (in your preferred language), data modeling, as well as data mining may also be asked.
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