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Undisclosed Senior Data Engineer Interview Questions and Answers

Updated 27 Jun 2024

Undisclosed Senior Data Engineer Interview Experiences

1 interview found

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 Dec 2023. There was 1 interview round.

Round 1 - One-on-one 

(2 Questions)

  • Q1. How would you trigger ADF pipeline?
  • Ans. 

    ADF pipelines can be triggered using triggers like schedule, event, manual, or tumbling window.

    • Use a schedule trigger to run the pipeline at specific times or intervals.

    • Use an event trigger to start the pipeline based on an event like a file being added to a storage account.

    • Manually trigger the pipeline through the ADF UI or REST API.

    • Tumbling window trigger can be used to run the pipeline at regular intervals based on

  • Answered by AI
  • Q2. How would you ensure that your ADF pipeline does not fail?
  • Ans. 

    To ensure ADF pipeline does not fail, monitor pipeline health, handle errors gracefully, optimize performance, and conduct regular testing.

    • Monitor pipeline health regularly to identify and address potential issues proactively

    • Handle errors gracefully by implementing error handling mechanisms such as retries, logging, and notifications

    • Optimize performance by tuning pipeline configurations, optimizing data processing logi...

  • Answered by AI

Skills evaluated in this interview

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
-

I applied via Recruitment Consulltant

Round 1 - Technical 

(5 Questions)

  • Q1. Explain ETL pipeline ecosystem in Azure Databricks?
  • Q2. Star vs Snowflake schema, when to use?
  • Q3. Find Salary higher than Average department salary
  • Q4. Implementation of SCD2 table
  • Q5. How incremental loading is done
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

The aptitude test lasts 30 minutes and focuses on topics relevant to data engineering, including Spark, SQL, Azure, and PySpark.

Round 2 - Coding Test 

The coding test is a one-hour examination on PySpark.

Round 3 - Technical 

(3 Questions)

  • Q1. What is the difference between Cache() and Persist()?
  • Q2. What does the purpose of the Spark Submit command in Apache Spark?
  • Q3. What are window functions in SQL?
Round 4 - HR 

(2 Questions)

  • Q1. Could you provide more details about the daily responsibilities associated with this role?
  • Q2. How would you describe your work culture?
Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
No response

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

Round 1 - Technical 

(6 Questions)

  • Q1. Can you introduce yourself and describe your current project experience?
  • Ans. 

    I am a Senior Data Engineer with experience in building scalable data pipelines and optimizing data processing workflows.

    • Experience in designing and implementing ETL processes using tools like Apache Spark and Airflow

    • Proficient in working with large datasets and optimizing query performance

    • Strong background in data modeling and database design

    • Worked on projects involving real-time data processing and streaming analytic

  • Answered by AI
  • Q2. Decorators in python
  • Ans. 

    Decorators in Python are functions that modify the behavior of other functions or methods.

    • Decorators are defined using the @decorator_name syntax before a function definition.

    • They can be used to add functionality to existing functions without modifying their code.

    • Decorators can be used for logging, timing, authentication, and more.

    • Example: @staticmethod decorator in Python is used to define a static method in a class.

  • Answered by AI
  • Q3. What is the SQL query to group by employee ID in order to combine the first name and last name with a space?
  • Ans. 

    SQL query to group by employee ID and combine first name and last name with a space

    • Use the GROUP BY clause to group by employee ID

    • Use the CONCAT function to combine first name and last name with a space

    • Select employee ID, CONCAT(first_name, ' ', last_name) AS full_name

  • Answered by AI
  • Q4. What are constructors in Python?
  • Ans. 

    Constructors in Python are special methods used for initializing objects. They are called automatically when a new instance of a class is created.

    • Constructors are defined using the __init__() method in a class.

    • They are used to initialize instance variables of a class.

    • Example: class Person: def __init__(self, name, age): self.name = name self.age = age person1 = Person('Alice', 30)

  • Answered by AI
  • Q5. Indexing in sql
  • Ans. 

    Indexing in SQL is a technique used to improve the performance of queries by creating a data structure that allows for faster retrieval of data.

    • Indexes are created on columns in a database table to speed up the retrieval of rows that match a certain condition in a WHERE clause.

    • Indexes can be created using CREATE INDEX statement in SQL.

    • Types of indexes include clustered indexes, non-clustered indexes, unique indexes, an...

  • Answered by AI
  • Q6. Why spark works well with parquet files?
  • Ans. 

    Spark works well with Parquet files due to its columnar storage format, efficient compression, and ability to push down filters.

    • Parquet files are columnar storage format, which aligns well with Spark's processing model of working on columns rather than rows.

    • Parquet files support efficient compression, reducing storage space and improving read performance in Spark.

    • Spark can push down filters to Parquet files, allowing f...

  • Answered by AI

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

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

Round 1 - Technical 

(2 Questions)

  • Q1. All questions based on databricks and some pyspark , python , SQL only.
  • Q2. Learn windows function implementation in databricks note book.
Round 2 - HR 

(1 Question)

  • Q1. This round about your salary discussion around.

Interview Preparation Tips

Topics to prepare for Accenture Senior Data Engineer interview:
  • Python
  • Pyspark
  • SQL
  • Databricks
Interview preparation tips for other job seekers - Please prepare for pyspark, python , SQL , databricks for practice to switch your job to big data engineer
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Sql query to write max salary
  • Ans. 

    Use SQL query with MAX function to find the highest salary in a table.

    • Use SELECT MAX(salary) FROM table_name;

    • Make sure to replace 'salary' with the actual column name in the table.

    • Ensure proper permissions to access the table.

  • Answered by AI
  • Q2. What is dense rank in sql
  • Ans. 

    Dense rank in SQL assigns a unique rank to each distinct row in a result set, with no gaps between the ranks.

    • Dense rank is used to assign a rank to each row in a result set without any gaps.

    • It differs from regular rank in that it does not skip ranks if there are ties.

    • For example, if two rows have the same value and are ranked 1st, the next row will be ranked 2nd, not 3rd.

  • Answered by AI
Round 2 - Technical 

(2 Questions)

  • Q1. What is spark cluster
  • Ans. 

    Spark cluster is a group of interconnected computers that work together to process large datasets using Apache Spark.

    • Consists of a master node and multiple worker nodes

    • Master node manages the distribution of tasks and resources

    • Worker nodes execute the tasks in parallel

    • Used for processing big data and running distributed computing jobs

  • Answered by AI
  • Q2. How hive works in hdfs
  • Ans. 

    Hive is a data warehouse system built on top of Hadoop for querying and analyzing large datasets stored in HDFS.

    • Hive translates SQL-like queries into MapReduce jobs to process data stored in HDFS

    • It uses a metastore to store metadata about tables and partitions

    • HiveQL is the query language used in Hive, similar to SQL

    • Hive supports partitioning, bucketing, and indexing for optimizing queries

  • Answered by AI

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I was interviewed in Aug 2024.

Round 1 - Coding Test 

Python and sql tasks

Round 2 - Technical 

(2 Questions)

  • Q1. Project related questions
  • Q2. Coding questions on pyspark windows
Round 3 - One-on-one 

(1 Question)

  • Q1. Managerial discussions, mostly in and around the previous projects
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I was interviewed in Sep 2024.

Round 1 - Technical 

(3 Questions)

  • Q1. Coding in pyspark
  • Ans. 

    Pyspark is a Python library for big data processing using Spark framework.

    • Pyspark is used for processing large datasets in parallel.

    • It provides APIs for data manipulation, querying, and analysis.

    • Example: Using pyspark to read a CSV file and perform data transformations.

  • Answered by AI
  • Q2. Databricks optimisation technique
  • Ans. 

    Databricks optimisation techniques improve performance and efficiency of data processing on the Databricks platform.

    • Use cluster sizing and autoscaling to optimize resource allocation based on workload

    • Leverage Databricks Delta for optimized data storage and processing

    • Utilize caching and persisting data to reduce computation time

    • Optimize queries by using appropriate indexing and partitioning strategies

  • Answered by AI
  • Q3. Aqe details in databricks
  • Ans. 

    Databricks is a unified data analytics platform that provides a collaborative environment for data engineers.

    • Databricks is built on top of Apache Spark and provides a workspace for data engineering tasks.

    • It allows for easy integration with various data sources and tools for data processing.

    • Databricks provides features like notebooks, clusters, and libraries for efficient data engineering workflows.

  • Answered by AI

Skills evaluated in this interview

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

(1 Question)

  • Q1. Adf,etl,python,adb
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

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

Round 1 - Coding Test 

Spark Optimization, Transformation, DLT, DL, Data Governance
Python
SQL

Interview Preparation Tips

Interview preparation tips for other job seekers - Ingestion, Integration, Spark, Optimization, Python, SQL, Data Warehouse

Undisclosed Interview FAQs

How many rounds are there in Undisclosed Senior Data Engineer interview?
Undisclosed interview process usually has 1 rounds. The most common rounds in the Undisclosed interview process are One-on-one Round.
What are the top questions asked in Undisclosed Senior Data Engineer interview?

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

  1. How would you ensure that your ADF pipeline does not fa...read more
  2. How would you trigger ADF pipeli...read more

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Undisclosed Senior Data Engineer Interview Process

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