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Cognizant Data Engineer Interview Questions and Answers

Updated 19 Apr 2025

28 Interview questions

A Data Engineer was asked 2mo ago
Q. Can you describe a tricky SQL question you have encountered?
Ans. 

SQL tricky questions often test your understanding of complex queries and data manipulation techniques.

  • Understand JOIN types: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN.

  • Use GROUP BY and HAVING clauses to aggregate data effectively.

  • Be familiar with window functions like ROW_NUMBER(), RANK(), and DENSE_RANK().

  • Practice writing subqueries and common table expressions (CTEs) for better readability.

  • Know how to h...

A Data Engineer was asked 6mo ago
Q. What are the different types of joins available in Spark?
Ans. 

Different types of joins in Spark include inner join, outer join, left join, right join, and full join.

  • Inner join: Returns only the rows that have matching values in both datasets.

  • Outer join: Returns all rows when there is a match in either dataset.

  • Left join: Returns all rows from the left dataset and the matched rows from the right dataset.

  • Right join: Returns all rows from the right dataset and the matched rows f...

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A Data Engineer was asked 7mo ago
Q. Explain the architecture of Delta Lake.
Ans. 

Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark and big data workloads.

  • Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing.

  • It stores data in Parquet format and uses Apache Spark for processing.

  • Delta Lake ensures data reliability and data quality by providing schema enforcement and data versioning.

  • It supports tim...

A Data Engineer was asked 11mo ago
Q. What do you mean by CDC?
Ans. 

CDC stands for Change Data Capture, a process of identifying and capturing changes made to data in a database.

  • CDC is used to track changes in data over time, allowing for real-time data integration and analysis.

  • It captures inserts, updates, and deletes made to data, providing a historical record of changes.

  • CDC is commonly used in data warehousing, data replication, and data integration processes.

  • Examples of CDC to...

What people are saying about Cognizant

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a junior software engineer
2w
Job offer in Malaysia - legit or scam?
Hey everyone, I received a job proposal from Mindgraph for a Junior Mainframe Developer position in Malaysia (onsite). Not sure if it's a real deal. They found my resume on Naukri and the offer includes: * Experience: 3+ years on cardlink, VSAM, CICS, JCL * Location: Malaysia (Accenture client in Kuala Lumpur) * Notice: 0-60 days * Benefits: One-way ticket, 1-week stay, medical insurance, visa. Has anyone heard of Mindgraph or had a similar experience? Note : This is a permanent position with Mindgragh and you need to work with our client Accenture - Malaysia (Kaula Lumpur) & we will provide one way Air Ticket from India - Malaysia, 1 Week Accommodation, Medical Insurance and will take care of the Visa process also. Any insights would be appreciated!
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A Data Engineer was asked 11mo ago
Q. How do you connect to S3 from Databricks?
Ans. 

To connect S3 from Databricks, you can use the AWS connector provided by Databricks.

  • Use the AWS connector provided by Databricks to connect to S3

  • Provide the necessary AWS credentials and S3 bucket details in the connector configuration

  • You can access S3 data using the file system API in Databricks

A Data Engineer was asked 11mo ago
Q. What is XCom in Airflow?
Ans. 

XCom in Airflow is a way for tasks to exchange messages or small amounts of data.

  • XCom allows tasks to communicate with each other by passing small pieces of data

  • It can be used to share information between tasks in a DAG

  • XCom can be used to pass information like task status, results, or any other data

A Data Engineer was asked
Q. What is a list in Python?
Ans. 

A list in Python is a collection of items that are ordered and mutable.

  • Lists are created using square brackets []

  • Items in a list can be of different data types

  • Lists can be modified by adding, removing, or changing items

  • Example: my_list = [1, 'apple', True]

Are these interview questions helpful?
A Data Engineer was asked
Q. What is the difference between coalesce and repartition?
Ans. 

Coalesce reduces the number of partitions in a DataFrame, while repartition increases the number of partitions.

  • Coalesce is used to reduce the number of partitions in a DataFrame without shuffling data

  • Repartition is used to increase the number of partitions in a DataFrame and can involve shuffling data

  • Coalesce is more efficient for reducing partitions when no data movement is required

  • Repartition is typically used f...

A Data Engineer was asked
Q. Pationong and bucket difference
Ans. 

Partitioning is dividing data into smaller chunks for better organization and performance, while bucketing is grouping data based on a specific criteria.

  • Partitioning is dividing data into smaller subsets based on a column or key.

  • Bucketing is grouping data based on a specific number of buckets or ranges.

  • Partitioning is commonly used in distributed systems for better data organization and query performance.

  • Bucketing...

A Data Engineer was asked
Q. What is the difference between flatMap and map?
Ans. 

Flat map is used to flatten nested arrays while map is used to transform each element in an array.

  • Flat map is used to flatten nested arrays into a single array.

  • Map is used to transform each element in an array using a function.

  • Flat map is commonly used in functional programming languages like JavaScript and Scala.

  • Map is a higher-order function that applies a given function to each element in an array.

Cognizant Data Engineer Interview Experiences

32 interviews found

Data Engineer Interview Questions & Answers

user image Abhishek Paithankar

posted on 16 Nov 2024

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

Aptitude test involved with quantative aptitude, logical reasoning and reading comprehensions.

Round 2 - Technical 

(2 Questions)

  • Q1. Tell me your introduction.
  • Q2. Tell me about your skills.
  • Ans. 

    I have strong skills in data processing, ETL, data modeling, and programming languages like Python and SQL.

    • Proficient in data processing and ETL techniques

    • Strong knowledge of data modeling and database design

    • Experience with programming languages like Python and SQL

    • Familiarity with big data technologies such as Hadoop and Spark

  • Answered by AI
Round 3 - HR 

(2 Questions)

  • Q1. Are you ready relocate,?
  • Ans. 

    Yes, I am open to relocating for the right opportunity.

    • I am willing to relocate for the right job opportunity.

    • I have experience moving for previous roles.

    • I am flexible and adaptable to new locations.

    • I am excited about the possibility of exploring a new city or country.

  • Answered by AI
  • Q2. Document verification

Interview Preparation Tips

Interview preparation tips for other job seekers - If you are fresher first prepare for aptitude, because once aptitude get cleared you will get selected from the large compitition and then focus on your technical knowledge and managerial skills about the company.

Data Engineer Interview Questions & Answers

user image Anonymous

posted on 22 Dec 2024

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Different types of Joins in spark
  • Ans. 

    Different types of joins in Spark include inner join, outer join, left join, right join, and full join.

    • Inner join: Returns only the rows that have matching values in both datasets.

    • Outer join: Returns all rows when there is a match in either dataset.

    • Left join: Returns all rows from the left dataset and the matched rows from the right dataset.

    • Right join: Returns all rows from the right dataset and the matched rows from t...

  • Answered by AI
  • Q2. Spark optimization techniques
  • Ans. 

    Optimization techniques in Spark improve performance and efficiency of data processing.

    • Partitioning data to distribute workload evenly

    • Caching frequently accessed data in memory

    • Using broadcast variables for small lookup tables

    • Avoiding shuffling operations whenever possible

  • Answered by AI

Skills evaluated in this interview

Data Engineer Interview Questions & Answers

user image Anonymous

posted on 13 Nov 2024

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Explain the architecture of delta lake
  • Ans. 

    Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark and big data workloads.

    • Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing.

    • It stores data in Parquet format and uses Apache Spark for processing.

    • Delta Lake ensures data reliability and data quality by providing schema enforcement and data versioning.

    • It supports time tra...

  • Answered by AI
  • Q2. Tuning operations in databricks
  • Ans. 

    Tuning operations in Databricks involves optimizing performance and efficiency of data processing tasks.

    • Use cluster configuration settings to allocate resources efficiently

    • Optimize code by minimizing data shuffling and reducing unnecessary operations

    • Leverage Databricks Auto Optimize to automatically tune performance

    • Monitor job performance using Databricks Runtime Metrics and Spark UI

  • Answered by AI

Skills evaluated in this interview

Data Engineer Interview Questions & Answers

user image Anonymous

posted on 11 Jul 2024

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
-
Result
No response

I applied via Approached by Company and was interviewed in Jun 2024. There was 1 interview round.

Round 1 - Technical 

(5 Questions)

  • Q1. Spark architecture
  • Q2. Spark optimization used in our project
  • Ans. 

    Spark optimization techniques used in project

    • Partitioning data to optimize parallel processing

    • Caching frequently accessed data to reduce computation time

    • Using broadcast variables for efficient data sharing across nodes

    • Optimizing shuffle operations to minimize data movement

    • Tuning memory and CPU settings for better performance

  • Answered by AI
  • Q3. What is XCom in Airflow
  • Ans. 

    XCom in Airflow is a way for tasks to exchange messages or small amounts of data.

    • XCom allows tasks to communicate with each other by passing small pieces of data

    • It can be used to share information between tasks in a DAG

    • XCom can be used to pass information like task status, results, or any other data

  • Answered by AI
  • Q4. How to connect S3 from Databricks
  • Ans. 

    To connect S3 from Databricks, you can use the AWS connector provided by Databricks.

    • Use the AWS connector provided by Databricks to connect to S3

    • Provide the necessary AWS credentials and S3 bucket details in the connector configuration

    • You can access S3 data using the file system API in Databricks

  • Answered by AI
  • Q5. What do you mean by CDC
  • Ans. 

    CDC stands for Change Data Capture, a process of identifying and capturing changes made to data in a database.

    • CDC is used to track changes in data over time, allowing for real-time data integration and analysis.

    • It captures inserts, updates, and deletes made to data, providing a historical record of changes.

    • CDC is commonly used in data warehousing, data replication, and data integration processes.

    • Examples of CDC tools i...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare well for basics of Spark, Databricks, Python and practice SQL.
Knowing any cloud technology will be an extra advantage.

Skills evaluated in this interview

Data Engineer Interview Questions & Answers

user image Sushwanth Yetigadda

posted on 19 Apr 2025

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

I appeared for an interview in Mar 2025, where I was asked the following questions.

  • Q1. Sql tricky ques
  • Ans. 

    SQL tricky questions often test your understanding of complex queries and data manipulation techniques.

    • Understand JOIN types: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN.

    • Use GROUP BY and HAVING clauses to aggregate data effectively.

    • Be familiar with window functions like ROW_NUMBER(), RANK(), and DENSE_RANK().

    • Practice writing subqueries and common table expressions (CTEs) for better readability.

    • Know how to handle...

  • Answered by AI
  • Q2. Dataframes ques

Data Engineer Interview Questions & Answers

user image Saloni Goswami

posted on 21 Aug 2024

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-

I applied via Campus Placement

Round 1 - One-on-one 

(2 Questions)

  • Q1. Why you want to join cognizant
  • Ans. 

    I want to join Cognizant because of its reputation for innovation and growth opportunities.

    • Cognizant is known for its cutting-edge technology solutions

    • I am impressed by Cognizant's commitment to employee development

    • I believe Cognizant will provide me with a challenging and rewarding work environment

  • Answered by AI
  • Q2. Why are you looking for only data engineer role.
  • Ans. 

    I am passionate about working with data and enjoy the challenges and opportunities that come with being a data engineer.

    • I have a strong background in data engineering and enjoy working with data processing technologies such as Hadoop, Spark, and Kafka.

    • I find data engineering to be a dynamic and evolving field that allows me to continuously learn and grow my skills.

    • I am excited about the impact that data engineering can...

  • Answered by AI

Data Engineer Interview Questions & Answers

user image Anonymous

posted on 20 Aug 2024

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Sql related questions
  • Q2. Hive related questions

Data Engineer Interview Questions & Answers

user image Anonymous

posted on 16 Feb 2024

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

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

Round 1 - One-on-one 

(3 Questions)

  • Q1. Word count by spark,, falt map and map difference
  • Ans. 

    Word count by spark, flatMap, and map difference

    • Spark is a distributed computing framework for big data processing

    • flatMap is used to split each input string into words

    • map is used to transform each word into a key-value pair for counting

    • The difference lies in how the data is processed and transformed

  • Answered by AI
  • Q2. Flat map and map difference
  • Ans. 

    Flat map is used to flatten nested arrays while map is used to transform each element in an array.

    • Flat map is used to flatten nested arrays into a single array.

    • Map is used to transform each element in an array using a function.

    • Flat map is commonly used in functional programming languages like JavaScript and Scala.

    • Map is a higher-order function that applies a given function to each element in an array.

  • Answered by AI
  • Q3. Pationong and bucket difference
  • Ans. 

    Partitioning is dividing data into smaller chunks for better organization and performance, while bucketing is grouping data based on a specific criteria.

    • Partitioning is dividing data into smaller subsets based on a column or key.

    • Bucketing is grouping data based on a specific number of buckets or ranges.

    • Partitioning is commonly used in distributed systems for better data organization and query performance.

    • Bucketing is o...

  • Answered by AI

Skills evaluated in this interview

Data Engineer Interview Questions & Answers

user image abhinav bagri

posted on 19 Nov 2024

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

50 MCQ for python SQL

Data Engineer Interview Questions & Answers

user image Pooja 2000

posted on 5 Mar 2025

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - HR 

(1 Question)

  • Q1. Are you okay with reallocation

Cognizant Interview FAQs

How many rounds are there in Cognizant Data Engineer interview?
Cognizant interview process usually has 1-2 rounds. The most common rounds in the Cognizant interview process are Technical, HR and Coding Test.
How to prepare for Cognizant 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 Cognizant. The most common topics and skills that interviewers at Cognizant expect are Python, SQL, Spark, AWS and Azure.
What are the top questions asked in Cognizant Data Engineer interview?

Some of the top questions asked at the Cognizant Data Engineer interview -

  1. What are all the issues you faced in your project? What is Global Parameter? Wh...read more
  2. What is the difference between supervised and unsupervised learni...read more
  3. How to find delta between two tables in S...read more
How long is the Cognizant Data Engineer interview process?

The duration of Cognizant Data Engineer interview process can vary, but typically it takes about less than 2 weeks to complete.

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Overall Interview Experience Rating

4/5

based on 37 interview experiences

Difficulty level

Easy 11%
Moderate 78%
Hard 11%

Duration

Less than 2 weeks 65%
2-4 weeks 29%
4-6 weeks 6%
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Cognizant Data Engineer Salary
based on 2.6k salaries
₹3.3 L/yr - ₹15.7 L/yr
25% less than the average Data Engineer Salary in India
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based on 166 reviews

3.5/5

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3.4

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2.8

Salary

3.2

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3.3

Company culture

2.6

Promotions

3.1

Work satisfaction

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