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Koantek Senior DBA and Data Engineer Interview Questions and Answers

Updated 27 Mar 2024

Koantek Senior DBA and Data Engineer Interview Experiences

1 interview found

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

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

Round 1 - Technical 

(1 Question)

  • Q1. Questions related to sql and python were asked mostly to check the logic part

Interview Preparation Tips

Interview preparation tips for other job seekers - Have proper understanding of advanced sql and moderate python

Interview questions from similar companies

Interview Questionnaire 

1 Question

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

    Spark has a master-slave architecture with a cluster manager and worker nodes.

    • Spark has a driver program that communicates with a cluster manager to allocate resources and schedule tasks.

    • The cluster manager can be standalone, Mesos, or YARN.

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

    • Spark can also utilize external data sources like Hadoop Distributed File System (HDFS) or Amazon S3.

    • Spark supports va...

  • Answered by AI

Skills evaluated in this interview

I applied via Walk-in and was interviewed before Feb 2020. There was 1 interview round.

Interview Questionnaire 

1 Question

  • Q1. Interview mainly asked about spark architecture.

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare well with the basic

I applied via Campus Placement and was interviewed before Jul 2020. There was 1 interview round.

Interview Questionnaire 

1 Question

  • Q1. Joined as a fresher, basic C program algo

Interview Preparation Tips

Interview preparation tips for other job seekers - Very easy to crack
Interview experience
4
Good
Difficulty level
Hard
Process Duration
-
Result
Not Selected

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

Round 1 - Coding Test 

This was my first campus drive,& it was one of the hardest one too.We had 3 coding problems for 60 mins.It was held on HackerRank & it was not so hard but not so easy for the beginners.
1)Lambda Sort
2) and 3) ques on SQL
It was different ques for each one.

Interview Preparation Tips

Topics to prepare for Junglee Games Data Engineer interview:
  • Python
  • MySQL
Interview preparation tips for other job seekers - Be code at SQL queries,this is more important and good at any one programming language be it Java or Python.
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. The interviewer asked all the concepts of pyspark, ETL and a code on dsa
Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Campus Placement and was interviewed before May 2022. 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 - Coding Test 

It was a coding round with sql ,python questions , few aptitude questions

Round 3 - Technical 

(2 Questions)

  • Q1. They asked few questions sql and python and few questions - depending on the role
  • Q2. BASIC SQL WHAT YOU HAD WRITTEN IN THE CODE
Round 4 - Technical 

(2 Questions)

  • Q1. They asked me few questions related to sql
  • Q2. BASIC PYTHON QUESTIONS LIKE WHAT YOU HAVE WRITTEN IN THE CODE
Round 5 - HR 

(1 Question)

  • Q1. About yourself , your hobby etc

Interview Preparation Tips

Interview preparation tips for other job seekers - be confident and be able to explain the code you wrote in coding round
Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed in May 2024. There were 4 interview rounds.

Round 1 - Coding Test 

Python and SQL questions were asked

Round 2 - One-on-one 

(1 Question)

  • Q1. I was asked about the project
Round 3 - One-on-one 

(1 Question)

  • Q1. ACID properties of DBMS
  • Ans. 

    ACID properties ensure data integrity in DBMS: Atomicity, Consistency, Isolation, Durability.

    • Atomicity ensures that all operations in a transaction are completed successfully or none at all.

    • Consistency ensures that the database remains in a consistent state before and after the transaction.

    • Isolation ensures that multiple transactions can be executed concurrently without affecting each other.

    • Durability ensures that once...

  • Answered by AI
Round 4 - HR 

(1 Question)

  • Q1. HR question and family background

Interview Preparation Tips

Topics to prepare for Junglee Games Data Engineer interview:
  • SQL
  • Python
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
3
Average
Difficulty level
-
Process Duration
-
Result
Not Selected

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

Round 1 - One-on-one 

(4 Questions)

  • Q1. Lazy evaluation narrow wide tranform data brick utlity functions
  • Q2. Dag,edges vertices
  • Q3. Spark architecture
  • Q4. Memory allocation

Koantek Interview FAQs

How many rounds are there in Koantek Senior DBA and Data Engineer interview?
Koantek interview process usually has 1 rounds. The most common rounds in the Koantek interview process are Technical.

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Koantek Senior DBA and Data Engineer Interview Process

based on 1 interview

Interview experience

4
  
Good
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