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Koantek Senior Data Engineer Interview Questions and Answers

Updated 31 May 2024

Koantek Senior Data Engineer Interview Experiences

6 interviews found

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
No response

I applied via Job Fair and was interviewed in May 2024. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. SQL query for root,leaf and other nodes Spark Optimizations Python Coding questions
Round 2 - Technical 

(1 Question)

  • Q1. About Project,Spark Questions, Optimizations, OOPS Concept. SQL Questions
Interview experience
3
Average
Difficulty level
Easy
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed in Aug 2023. There were 3 interview rounds.

Round 1 - Technical 

(2 Questions)

  • Q1. Pretty simple and basic spark, very easy to crack, just be confident
  • Q2. Project discussion
Round 2 - Technical 

(1 Question)

  • Q1. Again a simple one, just need to know to basics of big data.
Round 3 - Behavioral 

(1 Question)

  • Q1. More on interpersonal skills and behavioral one

Senior Data Engineer Interview Questions Asked at Other Companies

asked in 7 Eleven
Q1. Write a query to get the customer with the highest total order va ... read more
asked in 7 Eleven
Q2. There are 10 million records in the table and the schema does not ... read more
asked in 7 Eleven
Q3. How do you handle data pipeline when the schema information keeps ... read more
asked in 7 Eleven
Q4. Difference between Parquet and ORC file. Why industry uses parque ... read more
asked in 7 Eleven
Q5. What is Normalisation and Denormalisation? When do we use them? G ... read more
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

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

Round 1 - HR 

(2 Questions)

  • Q1. Basic questions around Data Engineering to check ad go through profile
  • Q2. Basic working of spark
  • Ans. 

    Spark is a distributed computing framework that provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.

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

    • 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.

    • It supports a wide range of data processing tasks, i...

  • Answered by AI
Round 2 - Coding Test 

Intermediate level Python and SQL question

Skills evaluated in this interview

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

I applied via Approached by Company and was interviewed in Jul 2023. There were 3 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Properly align and format text in your resume. A recruiter will have to spend more time reading poorly aligned text, leading to high chances of rejection.
View all tips
Round 2 - Aptitude Test 

Cultural discussion and briefing on job description

Round 3 - Coding Test 

SQL logic test and pipeline design

Interview Preparation Tips

Topics to prepare for Koantek Senior Data Engineer interview:
  • SQL
  • ETL
Interview preparation tips for other job seekers - Just be honest on what you know and what you have been doing. If you don't know what you are asked to answer, don't pretend to know but be frank on answering.

Koantek interview questions for designations

 Data Engineer

 (8)

 Senior DBA and Data Engineer

 (1)

 Data Scientist

 (1)

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

I applied via Recruitment Consulltant and was interviewed before Jan 2022. There were 4 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 - Coding Test 

Coding skills in Python, Spark/Scala are a must.

Round 3 - Coding Test 

Python, Spark, Scala, Terraform

Round 4 - One-on-one 

(2 Questions)

  • Q1. Why are you changing the job
  • Q2. What is your strong suite

Interview Preparation Tips

Interview preparation tips for other job seekers - Coding skills are a must. Cannot survive without that.
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed before Mar 2022. There were 3 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Don’t add your photo or details such as gender, age, and address in your resume. These details do not add any value.
View all tips
Round 2 - Aptitude Test 

The aptitude test was not that difficult.

Round 3 - Coding Test 

The coding test was of moderate difficulty

Interview Preparation Tips

Topics to prepare for Koantek Senior Data Engineer interview:
  • SQL
  • Python
Interview preparation tips for other job seekers - Study the data related concepts of SQL and python thoroughly to get this job.

Interview questions from similar companies

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

(3 Questions)

  • Q1. ReduceByKey vs groupByKey
  • Ans. 

    reduceByKey is more efficient than groupByKey for aggregating data in Spark due to reduced shuffling.

    • reduceByKey combines values for each key in each partition before shuffling data

    • groupByKey shuffles all data to a single partition before combining values for each key

    • reduceByKey is preferred for large datasets to minimize data movement and improve performance

  • Answered by AI
  • Q2. Word count in scala
  • Ans. 

    Scala provides a simple way to count words in a string using built-in functions.

    • Use the split function to split the string into an array of words

    • Use the length function to get the count of words in the array

  • Answered by AI
  • Q3. Second highest salary SQL
  • Ans. 

    Use SQL query with ORDER BY and LIMIT to find the second highest salary.

    • Use ORDER BY clause to sort salaries in descending order

    • Use LIMIT 1,1 to skip the first highest salary and get the second highest salary

  • Answered by AI

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed before Jun 2023. There were 3 interview rounds.

Round 1 - One-on-one 

(2 Questions)

  • Q1. It’s general type of question
  • Q2. Experience n all
Round 2 - Group Discussion 

It’s just reasoning type questions.

Round 3 - Technical 

(2 Questions)

  • Q1. What is ssis? How we use
  • Ans. 

    SSIS stands for SQL Server Integration Services, a tool provided by Microsoft for data integration and workflow applications.

    • SSIS is a platform for building high-performance data integration and workflow solutions.

    • It allows you to create packages that move data from various sources to destinations.

    • SSIS includes a visual design interface for creating, monitoring, and managing data integration processes.

    • You can use SSIS ...

  • Answered by AI
  • Q2. When we use ssis packages? Difference between union merge
  • Ans. 

    SSIS packages are used for ETL processes in SQL Server. Union combines datasets vertically, while merge combines them horizontally.

    • SSIS packages are used for Extract, Transform, Load (ETL) processes in SQL Server.

    • Union in SSIS combines datasets vertically, stacking rows on top of each other.

    • Merge in SSIS combines datasets horizontally, matching rows based on specified columns.

    • Union All in SSIS combines datasets vertica...

  • Answered by AI

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

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

Round 1 - Technical 

(12 Questions)

  • Q1. Tell me about yourself and Project
  • Ans. 

    I am a Senior Data Engineer with experience in developing data pipelines and optimizing data storage for various projects.

    • Developed data pipelines using Apache Spark for real-time data processing

    • Optimized data storage using technologies like Hadoop and AWS S3

    • Worked on a project to analyze customer behavior and improve marketing strategies

  • Answered by AI
  • Q2. What was you day-to-day job in your project
  • Ans. 

    My day-to-day job in the project involved designing and implementing data pipelines, optimizing data workflows, and collaborating with cross-functional teams.

    • Designing and implementing data pipelines to extract, transform, and load data from various sources

    • Optimizing data workflows to improve efficiency and performance

    • Collaborating with cross-functional teams including data scientists, analysts, and business stakeholde...

  • Answered by AI
  • Q3. Spark Architecture
  • Q4. How DAG handle Fault tolerance?
  • Ans. 

    DAGs handle fault tolerance by rerunning failed tasks and maintaining task dependencies.

    • DAGs rerun failed tasks automatically to ensure completion.

    • DAGs maintain task dependencies to ensure proper sequencing.

    • DAGs can be configured to retry failed tasks a certain number of times before marking them as failed.

  • Answered by AI
  • Q5. What is shuffling? How to Handle Shuffling?
  • Ans. 

    Shuffling is the process of redistributing data across partitions in a distributed computing environment.

    • Shuffling is necessary when data needs to be grouped or aggregated across different partitions.

    • It can be handled efficiently by minimizing the amount of data being shuffled and optimizing the partitioning strategy.

    • Techniques like partitioning, combiners, and reducers can help reduce the amount of shuffling in MapRed

  • Answered by AI
  • Q6. What is the difference between repartition and Coelsce?
  • Ans. 

    Repartition increases or decreases the number of partitions in a DataFrame, while Coalesce only decreases the number of partitions.

    • Repartition can increase or decrease the number of partitions in a DataFrame, leading to a shuffle of data across the cluster.

    • Coalesce only decreases the number of partitions in a DataFrame without performing a full shuffle, making it more efficient than repartition.

    • Repartition is typically...

  • Answered by AI
  • Q7. How do you handle Incremental data?
  • Ans. 

    Incremental data is handled by identifying new data since the last update and merging it with existing data.

    • Identify new data since last update

    • Merge new data with existing data

    • Update data warehouse or database with incremental changes

  • Answered by AI
  • Q8. What is SCD ??
  • Ans. 

    SCD stands for Slowly Changing Dimension, a concept in data warehousing to track changes in data over time.

    • SCD is used to maintain historical data in a data warehouse.

    • There are three types of SCD - Type 1, Type 2, and Type 3.

    • Type 1 SCD overwrites old data with new data.

    • Type 2 SCD creates a new record for each change, preserving history.

    • Type 3 SCD maintains both old and new values in the same record.

    • SCD is important for...

  • Answered by AI
  • Q9. Scenerio based questions related to Spark ?
  • Q10. Two SQL Codes and Two Python codes like reverse a string ?
  • Ans. 

    Reverse a string using SQL and Python codes.

    • In SQL, use the REVERSE function to reverse a string.

    • In Python, use slicing with a step of -1 to reverse a string.

  • Answered by AI
  • Q11. Find top 5 countries with highest population in Spark and SQL
  • Ans. 

    Use Spark and SQL to find the top 5 countries with the highest population.

    • Use Spark to load the data and perform data processing.

    • Use SQL queries to group by country and sum the population.

    • Order the results in descending order and limit to top 5.

    • Example: SELECT country, SUM(population) AS total_population FROM table_name GROUP BY country ORDER BY total_population DESC LIMIT 5

  • Answered by AI
  • Q12. Using two tables find the different records for different joins
  • Ans. 

    To find different records for different joins using two tables

    • Use the SQL query to perform different joins like INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN

    • Identify the key columns in both tables to join on

    • Select the columns from both tables and use WHERE clause to filter out the different records

  • Answered by AI
Round 2 - One-on-one 

(7 Questions)

  • Q1. What is a catalyst optimiser? How it works?
  • Ans. 

    A catalyst optimizer is a query optimization tool used in Apache Spark to improve performance by generating an optimal query plan.

    • Catalyst optimizer is a rule-based query optimization framework in Apache Spark.

    • It leverages rules to transform the logical query plan into a more optimized physical plan.

    • The optimizer applies various optimization techniques like predicate pushdown, constant folding, and join reordering.

    • By o...

  • Answered by AI
  • Q2. Tell me about the optimization you used in your project.
  • Ans. 

    Used query optimization techniques to improve performance in database queries.

    • Utilized indexing to speed up search queries.

    • Implemented query caching to reduce redundant database calls.

    • Optimized SQL queries by restructuring joins and subqueries.

    • Utilized database partitioning to improve query performance.

    • Used query profiling tools to identify and optimize slow queries.

  • Answered by AI
  • Q3. Pyspark question related to merging two schemas?
  • Q4. What is the best approach to finding whether the data frame is empty or not?
  • Ans. 

    Use the len() function to check the length of the data frame.

    • Use len() function to get the number of rows in the data frame.

    • If the length is 0, then the data frame is empty.

    • Example: if len(df) == 0: print('Data frame is empty')

  • Answered by AI
  • Q5. Spark Architecture
  • Q6. How do you decide on cores and worker nodes?
  • Ans. 

    Cores and worker nodes are decided based on the workload requirements and scalability needs of the data processing system.

    • Consider the size and complexity of the data being processed

    • Evaluate the processing speed and memory requirements of the tasks

    • Take into account the parallelism and concurrency needed for efficient data processing

    • Monitor the system performance and adjust cores and worker nodes as needed

  • Answered by AI
  • Q7. What happens when we enforce schema ?
  • Ans. 

    Enforcing schema ensures that data conforms to a predefined structure and rules.

    • Ensures data integrity by validating incoming data against predefined schema

    • Helps in maintaining consistency and accuracy of data

    • Prevents data corruption and errors in data processing

    • Can lead to rejection of data that does not adhere to the schema

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Persistent Systems Senior Data Engineer interview:
  • SQL
  • Pyspark
  • Python
  • Spark
  • Database
Interview preparation tips for other job seekers - Be prepared with Spark core concepts and SQL Coding

Skills evaluated in this interview

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

Big data and sql,python related questions

Round 2 - Technical 

(1 Question)

  • Q1. Big data and python related questions
Round 3 - HR 

(1 Question)

  • Q1. Previous company questions and general HR questions

Koantek Interview FAQs

How many rounds are there in Koantek Senior Data Engineer interview?
Koantek interview process usually has 2-3 rounds. The most common rounds in the Koantek interview process are Coding Test, Technical and Resume Shortlist.
How to prepare for Koantek Senior 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 Koantek. The most common topics and skills that interviewers at Koantek expect are Python, Spark, Streaming, SQL and AWS.
What are the top questions asked in Koantek Senior Data Engineer interview?

Some of the top questions asked at the Koantek Senior Data Engineer interview -

  1. basic working of sp...read more
  2. Pretty simple and basic spark, very easy to crack, just be confid...read more
  3. Again a simple one, just need to know to basics of big da...read more

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Koantek Senior Data Engineer Interview Process

based on 7 interviews

2 Interview rounds

  • Resume Shortlist Round
  • Coding Test Round
View more
Koantek Senior Data Engineer Salary
based on 29 salaries
₹16.8 L/yr - ₹31.5 L/yr
26% more than the average Senior Data Engineer Salary in India
View more details

Koantek Senior Data Engineer Reviews and Ratings

based on 7 reviews

4.0/5

Rating in categories

4.6

Skill development

3.7

Work-life balance

4.2

Salary

2.4

Job security

3.8

Company culture

3.3

Promotions

3.7

Work satisfaction

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