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PwC Big Data Engineer Interview Questions and Answers

Updated 18 Jul 2024

10 Interview questions

A Big Data Engineer was asked 11mo ago
Q. Explain Rank, Dense_rank, and row_number.
Ans. 

Rank, Dense_rank, and row_number are window functions used in SQL to assign a rank to each row based on a specified order.

  • Rank function assigns a unique rank to each row based on the specified order.

  • Dense_rank function assigns a unique rank to each row without any gaps based on the specified order.

  • Row_number function assigns a unique sequential integer to each row based on the specified order.

A Big Data Engineer was asked 11mo ago
Q. What are the core components of Spark?
Ans. 

Core components of Spark include Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX.

  • Spark Core: foundation of the Spark platform, provides basic functionality for distributed data processing

  • Spark SQL: module for working with structured data using SQL and DataFrame API

  • Spark Streaming: extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams

  • ...

Big Data Engineer Interview Questions Asked at Other Companies

Q1. Difference between partitioning and bucketing. Types of joins in ... read more
asked in TCS
Q2. What optimization techniques have you utilized in your projects? ... read more
Q3. Given the following data: col1 100 100 200 200 300 400 400 400 Us ... read more
Q4. Write a program to check if a Fibonacci number is present within ... read more
asked in TCS
Q5. What is the difference between lineage and directed acyclic graph ... read more
A Big Data Engineer was asked 11mo ago
Q. What is partitioning in Hive?
Ans. 

Partition in Hive is a way to organize data in a table into multiple directories based on the values of one or more columns.

  • Partitions help in improving query performance by allowing Hive to only read the relevant data directories.

  • Partitions are defined when creating a table in Hive using the PARTITIONED BY clause.

  • Example: CREATE TABLE table_name (column1 INT, column2 STRING) PARTITIONED BY (column3 STRING);

A Big Data Engineer was asked 11mo ago
Q. What is the architecture of Hive?
Ans. 

Hive Architecture is a data warehousing infrastructure built on top of Hadoop for querying and analyzing large datasets.

  • Hive uses a language called HiveQL which is similar to SQL for querying data stored in Hadoop.

  • It organizes data into tables, partitions, and buckets to optimize queries and improve performance.

  • Hive metastore stores metadata about tables, columns, partitions, and their locations.

  • Hive queries are c...

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a senior analyst
4d
Microsoft Assessment coming up—any prep tips?
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A Big Data Engineer was asked 11mo ago
Q. If we have streaming data coming from Kafka and Spark, how will you handle fault tolerance?
Ans. 

Implement fault tolerance by using checkpointing, replication, and monitoring mechanisms.

  • Enable checkpointing in Spark Streaming to save the state of the computation periodically to a reliable storage like HDFS or S3.

  • Use replication in Kafka to ensure that data is not lost in case of node failures.

  • Monitor the health of the Kafka and Spark clusters using tools like Prometheus and Grafana to detect and address issue...

A Big Data Engineer was asked 11mo ago
Q. What is Apache Spark?
Ans. 

Apache Spark is an open-source distributed computing system that provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.

  • Apache Spark is designed for speed and ease of use in processing large amounts of data.

  • It can run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk.

  • Spark provides high-level APIs in Java, Scala, Python, and R, and a...

A Big Data Engineer was asked 11mo ago
Q. What are functions in SQL?
Ans. 

Functions in SQL are built-in operations that can be used to manipulate data or perform calculations within a database.

  • Functions in SQL can be used to perform operations on data, such as mathematical calculations, string manipulation, date/time functions, and more.

  • Examples of SQL functions include SUM(), AVG(), CONCAT(), UPPER(), LOWER(), DATE_FORMAT(), and many others.

  • Functions can be used in SELECT statements, W...

Are these interview questions helpful?
A Big Data Engineer was asked 11mo ago
Q. If you have a large dataset to load that will not fit into memory, how would you load the file?
Ans. 

Use techniques like chunking, streaming, or distributed processing to load large datasets that exceed memory limits.

  • Chunking: Load data in smaller, manageable pieces. For example, using pandas in Python: pd.read_csv('file.csv', chunksize=1000).

  • Streaming: Process data on-the-fly without loading it all into memory. Use libraries like Dask or Apache Kafka.

  • Distributed Processing: Utilize frameworks like Apache Spark o...

A Big Data Engineer was asked 11mo ago
Q. What are your preferred methods for vectorization?
Ans. 

Vectorization is the process of converting data into a numerical format for efficient processing and analysis.

  • Vectorization improves performance by enabling parallel processing.

  • In machine learning, it converts text data into numerical vectors (e.g., TF-IDF).

  • In image processing, it transforms pixel data into feature vectors for analysis.

  • Libraries like NumPy in Python facilitate vectorization for numerical computati...

A Big Data Engineer was asked 11mo ago
Q. What is vectorization in ?
Ans. 

Vectorization is the process of converting data into a format that can be easily processed by a computer's CPU or GPU.

  • Vectorization allows for parallel processing of data, improving computational efficiency.

  • It involves performing operations on entire arrays or matrices at once, rather than on individual elements.

  • Examples include using libraries like NumPy in Python to perform vectorized operations on arrays.

  • Vector...

PwC Big Data Engineer Interview Experiences

1 interview found

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
-

I applied via Naukri.com and was interviewed in Jun 2024. There was 1 interview round.

Round 1 - One-on-one 

(11 Questions)

  • Q1. Working Experienace in current project
  • Q2. If i have large dataset to load which will not fit into the memory, How will you load the file?
  • Ans. 

    Use techniques like chunking, streaming, or distributed processing to load large datasets that exceed memory limits.

    • Chunking: Load data in smaller, manageable pieces. For example, using pandas in Python: pd.read_csv('file.csv', chunksize=1000).

    • Streaming: Process data on-the-fly without loading it all into memory. Use libraries like Dask or Apache Kafka.

    • Distributed Processing: Utilize frameworks like Apache Spark or Had...

  • Answered by AI
  • Q3. What is Apache spark?
  • Ans. 

    Apache Spark is an open-source distributed computing system that provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.

    • Apache Spark is designed for speed and ease of use in processing large amounts of data.

    • It can run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk.

    • Spark provides high-level APIs in Java, Scala, Python, and R, and an opt...

  • Answered by AI
  • Q4. What are core components of spark?
  • Ans. 

    Core components of Spark include Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX.

    • Spark Core: foundation of the Spark platform, provides basic functionality for distributed data processing

    • Spark SQL: module for working with structured data using SQL and DataFrame API

    • Spark Streaming: extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams

    • MLlib...

  • Answered by AI
  • Q5. If we have streaming data coming from kafka and spark , how will you handle fault tolerance?
  • Ans. 

    Implement fault tolerance by using checkpointing, replication, and monitoring mechanisms.

    • Enable checkpointing in Spark Streaming to save the state of the computation periodically to a reliable storage like HDFS or S3.

    • Use replication in Kafka to ensure that data is not lost in case of node failures.

    • Monitor the health of the Kafka and Spark clusters using tools like Prometheus and Grafana to detect and address issues pro...

  • Answered by AI
  • Q6. What is hive Architecture?
  • Ans. 

    Hive Architecture is a data warehousing infrastructure built on top of Hadoop for querying and analyzing large datasets.

    • Hive uses a language called HiveQL which is similar to SQL for querying data stored in Hadoop.

    • It organizes data into tables, partitions, and buckets to optimize queries and improve performance.

    • Hive metastore stores metadata about tables, columns, partitions, and their locations.

    • Hive queries are conver...

  • Answered by AI
  • Q7. What is vectorization in ?
  • Ans. 

    Vectorization is the process of converting data into a format that can be easily processed by a computer's CPU or GPU.

    • Vectorization allows for parallel processing of data, improving computational efficiency.

    • It involves performing operations on entire arrays or matrices at once, rather than on individual elements.

    • Examples include using libraries like NumPy in Python to perform vectorized operations on arrays.

    • Vectorizati...

  • Answered by AI
  • Q8. We have to do Vectorization?
  • Ans. 

    Vectorization is the process of converting data into a numerical format for efficient processing and analysis.

    • Vectorization improves performance by enabling parallel processing.

    • In machine learning, it converts text data into numerical vectors (e.g., TF-IDF).

    • In image processing, it transforms pixel data into feature vectors for analysis.

    • Libraries like NumPy in Python facilitate vectorization for numerical computations.

  • Answered by AI
  • Q9. What is partition in hive?
  • Ans. 

    Partition in Hive is a way to organize data in a table into multiple directories based on the values of one or more columns.

    • Partitions help in improving query performance by allowing Hive to only read the relevant data directories.

    • Partitions are defined when creating a table in Hive using the PARTITIONED BY clause.

    • Example: CREATE TABLE table_name (column1 INT, column2 STRING) PARTITIONED BY (column3 STRING);

  • Answered by AI
  • Q10. What are functions in SQL?
  • Ans. 

    Functions in SQL are built-in operations that can be used to manipulate data or perform calculations within a database.

    • Functions in SQL can be used to perform operations on data, such as mathematical calculations, string manipulation, date/time functions, and more.

    • Examples of SQL functions include SUM(), AVG(), CONCAT(), UPPER(), LOWER(), DATE_FORMAT(), and many others.

    • Functions can be used in SELECT statements, WHERE ...

  • Answered by AI
  • Q11. Explain Rank, Dense_rank , row_number
  • Ans. 

    Rank, Dense_rank, and row_number are window functions used in SQL to assign a rank to each row based on a specified order.

    • Rank function assigns a unique rank to each row based on the specified order.

    • Dense_rank function assigns a unique rank to each row without any gaps based on the specified order.

    • Row_number function assigns a unique sequential integer to each row based on the specified order.

  • Answered by AI

Skills evaluated in this interview

Interview questions from similar companies

I applied via Recruitment Consultant and was interviewed in Apr 2021. There were 4 interview rounds.

Interview Questionnaire 

3 Questions

  • Q1. Business Case Study., ETL Data warehouse scenarios , Advance SQL, ER diagram.
  • Q2. Rolling Sum calculations, SCD type 2, SCD type 1.
  • Q3. Spark Architecture.

Interview Preparation Tips

Interview preparation tips for other job seekers - Read Datawarehouse concept throughly, Solve Business case available over internet.
Good communication skills is mandatory. Be honest. Prepare your project details.

Big Data Engineer Interview Questions Asked at Other Companies

Q1. Difference between partitioning and bucketing. Types of joins in ... read more
asked in TCS
Q2. What optimization techniques have you utilized in your projects? ... read more
Q3. Given the following data: col1 100 100 200 200 300 400 400 400 Us ... read more
Q4. Write a program to check if a Fibonacci number is present within ... read more
asked in TCS
Q5. What is the difference between lineage and directed acyclic graph ... read more
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Not Selected

I applied via Company Website and was interviewed in Aug 2024. There were 2 interview rounds.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Project related discussions
  • Q2. Meduim level SQl and DSA
Round 2 - One-on-one 

(2 Questions)

  • Q1. This was data modelling round
  • Q2. Design a uber data model
  • Ans. 

    Uber data model design for efficient storage and retrieval of ride-related information.

    • Create tables for users, drivers, rides, payments, and ratings

    • Include attributes like user_id, driver_id, ride_id, payment_id, rating_id, timestamp, location, fare, etc.

    • Establish relationships between tables using foreign keys

    • Implement indexing for faster query performance

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare SQl, Python and data modeling

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Indeed and was interviewed in May 2023. There were 5 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Technical 

(1 Question)

  • Q1. Basics of python, SQL and pyspark
Round 3 - Technical 

(1 Question)

  • Q1. Questions on Python, SQL
Round 4 - Case Study 

PySpark questions to solve

Round 5 - Technical 

(1 Question)

  • Q1. Architectural questions

Interview Preparation Tips

Interview preparation tips for other job seekers - They expect you hold knowledge on everything from architecture to basics

What people are saying about PwC

View All
a senior analyst
4d
Microsoft Assessment coming up—any prep tips?
Hey everyone, I have a Microsoft Assessment coming up. If you have any insights or advice on how to prepare, please share!
Got a question about PwC?
Ask anonymously on communities.
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I appeared for an interview before Feb 2024.

Round 1 - Coding Test 

It was section wise, MCQ, then coding questions

Round 2 - Technical 

(2 Questions)

  • Q1. Questions related to tableau
  • Q2. Can you describe your project experience?
  • Ans. 

    I have experience working on projects involving data pipeline development, ETL processes, and data analysis.

    • Developed data pipelines using tools like Apache Spark and Airflow

    • Implemented ETL processes to extract, transform, and load data from various sources

    • Performed data analysis to derive insights and support decision-making

    • Worked on optimizing data storage and retrieval for improved performance

  • Answered by AI
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Data warehouse concepts
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
-
Result
Not Selected

I appeared for an interview in Sep 2023.

Round 1 - Technical 

(1 Question)

  • Q1. When the interview get started, interviewer directly jump into python coding questions based on the dict, arrays and lists. And then asked about some question data ware houses on SCD, Data Modeling,...etc....
Are these interview questions helpful?
Interview experience
2
Poor
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Company Website and was interviewed in Apr 2024. There was 1 interview round.

Round 1 - HR 

(2 Questions)

  • Q1. Present yourself
  • Q2. Asks about level of experience in each tachnology in the CV
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. The interiew was around for 1 hr asked python, sql airflow and data warehouse quetion
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
No response

I applied via Company Website and was interviewed in Dec 2023. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. Difference between list and tuple?
  • Ans. 

    List is mutable, tuple is immutable in Python.

    • List can be modified after creation, tuple cannot.

    • List is defined using square brackets [], tuple using parentheses ().

    • Example: list_example = [1, 2, 3], tuple_example = (4, 5, 6)

  • Answered by AI

Skills evaluated in this interview

PwC Interview FAQs

How many rounds are there in PwC Big Data Engineer interview?
PwC interview process usually has 1 rounds. The most common rounds in the PwC interview process are One-on-one Round.
How to prepare for PwC Big Data Engineer interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at PwC. The most common topics and skills that interviewers at PwC expect are Python, SQL, Big Data, Spark and Hadoop.
What are the top questions asked in PwC Big Data Engineer interview?

Some of the top questions asked at the PwC Big Data Engineer interview -

  1. If we have streaming data coming from kafka and spark , how will you handle fa...read more
  2. If i have large dataset to load which will not fit into the memory, How will y...read more
  3. What are core components of spa...read more

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Overall Interview Experience Rating

3/5

based on 1 interview experience

Difficulty level

Moderate 100%

Duration

Less than 2 weeks 100%
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PwC Big Data Engineer Salary
based on 23 salaries
₹6 L/yr - ₹22 L/yr
17% more than the average Big Data Engineer Salary in India
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3.0/5

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1.4

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3.2

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Company culture

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Promotions

2.2

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