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Coforge Data Engineer Interview Questions and Answers

Updated 6 Dec 2024

Coforge Data Engineer Interview Experiences

3 interviews found

Interview experience
4
Good
Difficulty level
Hard
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed before Jan 2023. There were 5 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Big data technologies
Round 2 - Technical 

(1 Question)

  • Q1. Detailed big data technologies
Round 3 - HR 

(3 Questions)

  • Q1. Salary discussion
  • Q2. Post confirmation hr declined discussed package and reduced it
  • Q3. Advise - Stick to said package only it’s their strategy otherwise decline to join
Round 4 - Technical 

(2 Questions)

  • Q1. Client technical round
  • Q2. Detailed project experience on mentioned Technologies
Round 5 - One-on-one 

(1 Question)

  • Q1. Again technically interviewed

Interview Preparation Tips

Topics to prepare for Coforge Data Engineer interview:
  • Spark
  • Big Data
  • Project
Interview preparation tips for other job seekers - If you have good offers in hand you may go ahead and join other companies
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 Nov 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Spark Architecture
  • Q2. Cache vs persist, lazy evaluation

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Data Engineer Interview Questions & Answers

user image Ravikumar Kawale (RK)

posted on 24 Aug 2023

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

I applied via LinkedIn and was interviewed in Jul 2023. There were 3 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. In round 1st they ask questions about your current project. Also the practical based questions on the modules you have worked in your recent project. Sometimes they ask to share ur screen. Overall experie...
Round 3 - Coding Test 

Python code and sql query they ask

Interview Preparation Tips

Interview preparation tips for other job seekers - First make good cv so then u will shortlist and after that HR will connect u. And further process goes smoothly

Data Engineer Jobs at Coforge

View all

Interview questions from similar companies

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Naukri.com and was interviewed in Oct 2024. There were 2 interview rounds.

Round 1 - Technical 

(7 Questions)

  • Q1. How do you optimize SQL queries?
  • Ans. 

    Optimizing SQL queries involves using indexes, avoiding unnecessary joins, and optimizing the query structure.

    • Use indexes on columns frequently used in WHERE clauses

    • Avoid using SELECT * and only retrieve necessary columns

    • Optimize joins by using INNER JOIN instead of OUTER JOIN when possible

    • Use EXPLAIN to analyze query performance and make necessary adjustments

  • Answered by AI
  • Q2. How do you do performance optimization in Spark. Tell how you did it in you project.
  • Ans. 

    Performance optimization in Spark involves tuning configurations, optimizing code, and utilizing caching.

    • Tune Spark configurations such as executor memory, number of executors, and shuffle partitions.

    • Optimize code by reducing unnecessary shuffles, using efficient transformations, and avoiding unnecessary data movements.

    • Utilize caching to store intermediate results in memory and avoid recomputation.

    • Example: In my projec...

  • Answered by AI
  • Q3. What is SparkContext and SparkSession?
  • Ans. 

    SparkContext is the main entry point for Spark functionality, while SparkSession is the entry point for Spark SQL.

    • SparkContext is the entry point for low-level API functionality in Spark.

    • SparkSession is the entry point for Spark SQL functionality.

    • SparkContext is used to create RDDs (Resilient Distributed Datasets) in Spark.

    • SparkSession provides a unified entry point for reading data from various sources and performing

  • Answered by AI
  • Q4. When a spark job is submitted, what happens at backend. Explain the flow.
  • Ans. 

    When a spark job is submitted, various steps are executed at the backend to process the job.

    • The job is submitted to the Spark driver program.

    • The driver program communicates with the cluster manager to request resources.

    • The cluster manager allocates resources (CPU, memory) to the job.

    • The driver program creates DAG (Directed Acyclic Graph) of the job stages and tasks.

    • Tasks are then scheduled and executed on worker nodes ...

  • Answered by AI
  • Q5. Calculate second highest salary using SQL as well as pyspark.
  • Ans. 

    Calculate second highest salary using SQL and pyspark

    • Use SQL query with ORDER BY and LIMIT to get the second highest salary

    • In pyspark, use orderBy() and take() functions to achieve the same result

  • Answered by AI
  • Q6. 2 types of modes for Spark architecture ?
  • Ans. 

    The two types of modes for Spark architecture are standalone mode and cluster mode.

    • Standalone mode: Spark runs on a single machine with a single JVM and is suitable for development and testing.

    • Cluster mode: Spark runs on a cluster of machines managed by a cluster manager like YARN or Mesos for production workloads.

  • Answered by AI
  • Q7. If you want very less latency - which is better standalone or client mode?
  • Ans. 

    Client mode is better for very less latency due to direct communication with the cluster.

    • Client mode allows direct communication with the cluster, reducing latency.

    • Standalone mode requires an additional layer of communication, increasing latency.

    • Client mode is preferred for real-time applications where low latency is crucial.

  • Answered by AI
Round 2 - Technical 

(2 Questions)

  • Q1. Scenario based. Write SQL and pyspark code for a dataset.
  • Q2. If you have to find latest record based on latest timestamp in a table for a particular customer(table is having history) , how will you do it. Self join and nested query will be expensive. Optimized query...

Interview Preparation Tips

Topics to prepare for LTIMindtree Data Engineer interview:
  • SQL
  • pyspark
  • ETL
Interview preparation tips for other job seekers - L2 was scheduled next day to L1 so the process is fast. Brush up your practical knowledge more.

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
No response
Round 1 - Technical 

(4 Questions)

  • Q1. What is the architecture of Apache Spark?
  • Ans. 

    Apache Spark architecture includes a cluster manager, worker nodes, and driver program.

    • Apache Spark architecture consists of a cluster manager, which allocates resources and schedules tasks.

    • Worker nodes execute tasks and store data in memory or disk.

    • Driver program coordinates tasks and communicates with the cluster manager.

    • Spark applications run as independent sets of processes on a cluster, coordinated by the SparkCon...

  • Answered by AI
  • Q2. What is the difference between the reduceBy and groupBy transformations in Apache Spark?
  • Ans. 

    reduceBy is used to aggregate data based on key, while groupBy is used to group data based on key.

    • reduceBy is a transformation that combines the values of each key using an associative function and a neutral 'zero value'.

    • groupBy is a transformation that groups the data based on a key and returns a grouped data set.

    • reduceBy is more efficient for aggregating data as it reduces the data before shuffling, while groupBy shu...

  • Answered by AI
  • Q3. What is the difference between RDD (Resilient Distributed Datasets) and DataFrame in Apache Spark?
  • Ans. 

    RDD is a low-level abstraction representing a distributed collection of objects, while DataFrame is a higher-level abstraction representing a distributed collection of data organized into named columns.

    • RDD is more suitable for unstructured data and low-level transformations, while DataFrame is more suitable for structured data and high-level abstractions.

    • DataFrames provide optimizations like query optimization and code...

  • Answered by AI
  • Q4. What are the different modes of execution in Apache Spark?
  • Ans. 

    The different modes of execution in Apache Spark include local mode, standalone mode, YARN mode, and Mesos mode.

    • Local mode: Spark runs on a single machine with one executor.

    • Standalone mode: Spark runs on a cluster managed by a standalone cluster manager.

    • YARN mode: Spark runs on a Hadoop cluster using YARN as the resource manager.

    • Mesos mode: Spark runs on a Mesos cluster with Mesos as the resource manager.

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

I applied via LinkedIn and was interviewed in Nov 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. How to Ensure Data loss in ETL pipeline
  • Q2. Why to spin up Dataproc cluster when there is serverless batch job exists.
Interview experience
2
Poor
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Campus Placement and was interviewed in Oct 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Write code in regular expression to remove the special characters
  • Ans. 

    Use regular expression to remove special characters from a string

    • Use the regex pattern [^a-zA-Z0-9\s] to match any character that is not a letter, digit, or whitespace

    • Use the replace() function in your programming language to replace the matched special characters with an empty string

    • Example: input string 'Hello! How are you?' will become 'Hello How are you' after removing special characters

  • Answered by AI
  • Q2. Questions on resume
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. What is Databricks, Internals of it, Optimization technique
  • Ans. 

    Databricks is a unified analytics platform that provides a collaborative environment for data scientists, engineers, and analysts.

    • Databricks is built on top of Apache Spark, providing a unified platform for data engineering, data science, and business analytics.

    • Internals of Databricks include a cluster manager, job scheduler, and workspace for collaboration.

    • Optimization techniques in Databricks include query optimizati...

  • Answered by AI
  • Q2. SQL questions of joins,group by
Round 2 - Technical 

(2 Questions)

  • Q1. Scenario based azure data factory questions
  • Q2. Project structres, pyspark dataframes related

Interview Preparation Tips

Interview preparation tips for other job seekers - Juat practice fundamentals

Skills evaluated in this interview

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

(1 Question)

  • Q1. Python SQL question
Round 2 - Technical 

(1 Question)

  • Q1. More on Project side
Round 3 - HR 

(1 Question)

  • Q1. Salary Discussion
Interview experience
1
Bad
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Data engineer roles and resposibilities

Interview Preparation Tips

Interview preparation tips for other job seekers - Don't Go, worst management service and lots of office politics.

Coforge Interview FAQs

How many rounds are there in Coforge Data Engineer interview?
Coforge interview process usually has 3 rounds. The most common rounds in the Coforge interview process are Technical, Resume Shortlist and Coding Test.
How to prepare for Coforge 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 Coforge. The most common topics and skills that interviewers at Coforge expect are Python, SQL, Spark, Data Warehousing and ETL.
What are the top questions asked in Coforge Data Engineer interview?

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

  1. In round 1st they ask questions about your current project. Also the practical...read more
  2. Advise - Stick to said package only it’s their strategy otherwise decline to ...read more
  3. Post confirmation hr declined discussed package and reduced...read more

Tell us how to improve this page.

Coforge Data Engineer Interview Process

based on 5 interviews

Interview experience

4.2
  
Good
View more
Coforge Data Engineer Salary
based on 115 salaries
₹4 L/yr - ₹29 L/yr
58% more than the average Data Engineer Salary in India
View more details

Coforge Data Engineer Reviews and Ratings

based on 9 reviews

3.1/5

Rating in categories

3.2

Skill development

2.9

Work-life balance

3.0

Salary

2.8

Job security

2.9

Company culture

2.4

Promotions

2.7

Work satisfaction

Explore 9 Reviews and Ratings
Data Engineer

Pune

5-10 Yrs

Not Disclosed

Looking For Data Engineers @ Coforge

Bangalore / Bengaluru,

Greater Noida

5-10 Yrs

Not Disclosed

Data Engineers ( AWS Serverless Architecture, Hadoop, Big Data)

Bangalore / Bengaluru

5-8 Yrs

₹ 15-30 LPA

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