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Incedo Data Engineer Interview Questions and Answers

Updated 14 Jan 2025

Incedo Data Engineer Interview Experiences

3 interviews found

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via LinkedIn and was interviewed in Mar 2024. There were 3 interview rounds.

Round 1 - Coding Test 

It was on cypher query language for me

Round 2 - Technical 

(1 Question)

  • Q1. Define Neo4J architecturaly
  • Ans. 

    Neo4J is a graph database management system that stores data in nodes and relationships.

    • Uses graph structures to represent and store data

    • Nodes represent entities and relationships represent connections between entities

    • Supports ACID transactions for data consistency

    • Query language is Cypher

  • Answered by AI
Round 3 - HR 

(1 Question)

  • Q1. Available location

Data Engineer Interview Questions & Answers

user image Anonymous

posted on 14 Jan 2025

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(1 Question)

  • Q1. Spark basic question , hive related questions.

Interview Preparation Tips

Interview preparation tips for other job seekers - Good question asked, It covers sql , spark and python.

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Data Engineer Interview Questions & Answers

user image Anonymous

posted on 30 Oct 2024

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

(1 Question)

  • Q1. Explain your project flow

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

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

Round 1 - One-on-one 

(2 Questions)

  • Q1. Azure Scenario based questions
  • Q2. Pyspark Coding based questions
Round 2 - One-on-one 

(2 Questions)

  • Q1. ADF, Databricks related question
  • Q2. Spark Performance problem and scenarios
  • Ans. 

    Spark performance problems can arise due to inefficient code, data skew, resource constraints, and improper configuration.

    • Inefficient code can lead to slow performance, such as using collect() on large datasets.

    • Data skew can cause uneven distribution of data across partitions, impacting processing time.

    • Resource constraints like insufficient memory or CPU can result in slow Spark jobs.

    • Improper configuration settings, su...

  • Answered by AI

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-

I applied via Campus Placement

Round 1 - Aptitude Test 

Based on SQL , statistics , python , cognitive

Round 2 - Technical 

(2 Questions)

  • Q1. Based on AI/Ml and based on cv
  • Q2. Based on projects
Round 3 - HR 

(2 Questions)

  • Q1. How to handle toxic work culture?
  • Ans. 

    Address toxic work culture by open communication, setting boundaries, seeking support, and considering leaving if necessary.

    • Open communication with colleagues and management about issues

    • Set boundaries to protect your mental and emotional well-being

    • Seek support from HR, a mentor, or a therapist if needed

    • Consider leaving the toxic work environment if the situation does not improve

  • Answered by AI
  • Q2. 5 strength and weakness

Interview Preparation Tips

Interview preparation tips for other job seekers - Be confident in interviews and try to calm ur mind!
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I was interviewed in Aug 2024.

Round 1 - Technical 

(5 Questions)

  • Q1. Questions on Pyspark
  • Q2. Questions on SQL
  • Q3. Transformations
  • Q4. Questions on Sql optimizations
  • Q5. Questions About my current Project
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
No response

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

Round 1 - One-on-one 

(2 Questions)

  • Q1. Incremental load in pyspark
  • Ans. 

    Incremental load in pyspark refers to loading only new or updated data into a dataset without reloading the entire dataset.

    • Use the 'delta' function in pyspark to perform incremental loads by specifying the 'mergeSchema' option.

    • Utilize the 'partitionBy' function to optimize incremental loads by partitioning the data based on specific columns.

    • Implement a logic to identify new or updated records based on timestamps or uni...

  • Answered by AI
  • Q2. Drop duplicates

Skills evaluated in this interview

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 Mar 2024. There were 2 interview rounds.

Round 1 - Coding Test 

Technical Assessment Test (MCQs) - 30 mins.

Round 2 - Technical 

(4 Questions)

  • Q1. Basic Questions on: 1.Python 2.SQL 3.Spark
  • Q2. Python: Replace all occurrences of word: "apple" with "froot" and count no.of occurrences of word: "apple" - in a given string (multiple lines) SQL: 1. Retrieve employee details, drawing the maximum salar...
  • Q3. Convert string (multiple lines) to list
  • Ans. 

    Use the split() method to convert a string with multiple lines into a list of strings.

    • Use the split() method with the newline character '\n' as the delimiter to split the string into a list of strings.

    • Example: 'Hello\nWorld\n' -> ['Hello', 'World']

  • Answered by AI
  • Q4. Convert string of multiple lines with 'n' words to multiple arrays of fixed size: k, with no overlap of elements accross arrays.
  • Ans. 

    Convert a string of multiple lines with 'n' words to multiple arrays of fixed size without overlap.

    • Split the string into individual words

    • Create arrays of fixed size 'k' and distribute words evenly

    • Handle cases where the number of words is not divisible by 'k'

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Altimetrik Data Engineer interview:
  • Python
  • SQL
  • PySpark

Skills evaluated in this interview

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

I applied via Campus Placement and was interviewed in Aug 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Java and sql questions

Round 2 - Coding Test 

Simple java program for find factorial and prime number

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

Basic aptitude and three levels of coding (easy,medium,hard)

Round 2 - Technical 

(1 Question)

  • Q1. Sql and java programming question
Round 3 - Technical 

(1 Question)

  • Q1. Advanced questions on sql and programming
Round 4 - HR 

(1 Question)

  • Q1. Normal hobbies and communication skills

Incedo Interview FAQs

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

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

  1. Define Neo4J architectur...read more
  2. spark basic question , hive related questio...read more
  3. Available locat...read more

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Incedo Data Engineer Interview Process

based on 3 interviews

Interview experience

3.7
  
Good
View more
Incedo Data Engineer Salary
based on 44 salaries
₹5 L/yr - ₹12.6 L/yr
29% less than the average Data Engineer Salary in India
View more details

Incedo Data Engineer Reviews and Ratings

based on 4 reviews

2.7/5

Rating in categories

2.6

Skill development

2.6

Work-life balance

2.9

Salary

2.3

Job security

2.6

Company culture

2.2

Promotions

2.2

Work satisfaction

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