NielsenIQ Data Engineer Interview Questions and Answers

Q1. What are different type of joins available in Databricks?
Ans. 
Different types of joins available in Databricks include inner join, outer join, left join, right join, and cross join.
• Inner join: Returns only the rows that have matching values in both tables.

• Outer join: Returns all rows when there is a match in either table.

• Left join: Returns all rows from the left table and the matched rows from the right table.

• Right join: Returns all rows from the right table and the matched rows ...read more
Answered by AI
Add your answer
Q2. How do you make your data pipeline fault tolerant?
Ans. 
Implementing fault tolerance in a data pipeline involves redundancy, monitoring, and error handling.
• Use redundant components to ensure continuous data flow

• Implement monitoring tools to detect failures and bottlenecks

• Set up automated alerts for immediate response to issues

• Design error handling mechanisms to gracefully handle failures

• Use checkpoints and retries to ensure data integrity
Answered by AI
Add your answer
Q3. What is AutoLoader?
Ans. 
AutoLoader is a feature in data engineering that automatically loads data from various sources into a data warehouse or database.
• Automates the process of loading data from different sources

• Reduces manual effort and human error

• Can be scheduled to run at specific intervals

• Examples: Apache Nifi, AWS Glue
Answered by AI
Add your answer

Q1. How do you connect to different services in Azure?
Ans. 
To connect to different services in Azure, you can use Azure SDKs, REST APIs, Azure Portal, Azure CLI, and Azure PowerShell.
• Use Azure SDKs for programming languages like Python, Java, C#, etc.

• Utilize REST APIs to interact with Azure services programmatically.

• Access and manage services through the Azure Portal.

• Leverage Azure CLI for command-line interface interactions.

• Automate tasks using Azure PowerShell scripts.
Answered by AI
Add your answer
Q2. What are linked Services?
Ans. 
Linked Services are connections to external data sources or destinations in Azure Data Factory.
• Linked Services define the connection information needed to connect to external data sources or destinations.

• They can be used in Data Factory pipelines to read from or write to external systems.

• Examples of Linked Services include Azure Blob Storage, Azure SQL Database, and Amazon S3.
Answered by AI
Add your answer

Q1. Difference between bigtable and bigquery.
Ans. 
Bigtable is a NoSQL database for real-time analytics, while BigQuery is a fully managed data warehouse for running SQL queries.
• Bigtable is a NoSQL database designed for real-time analytics and high throughput, while BigQuery is a fully managed data warehouse for running SQL queries.

• Bigtable is used for storing large amounts of semi-structured data, while BigQuery is used for analyzing structured data using SQL queries.

• ...read more
Answered by AI
Add your answer
Q2. How to remove duplicate rows from bigquery? find the month of a given date in bigquery.
Ans. 
To remove duplicate rows from BigQuery, use the DISTINCT keyword. To find the month of a given date, use the EXTRACT function.
• To remove duplicate rows, use SELECT DISTINCT * FROM table_name;

• To find the month of a given date, use SELECT EXTRACT(MONTH FROM date_column) AS month_name FROM table_name;

• Make sure to replace 'table_name' and 'date_column' with the appropriate values in your query.
Answered by AI
Add your answer
Q3. What operator is used in composer to move data from gcs to bq
Ans. 
The operator used in Composer to move data from GCS to BigQuery is the GCS to BigQuery operator.
• The GCS to BigQuery operator is used in Apache Airflow, which is the underlying technology of Composer.

• This operator allows you to transfer data from Google Cloud Storage (GCS) to BigQuery.

• You can specify the source and destination parameters in the operator to define the data transfer process.
Answered by AI
Add your answer
Q4. Write a code for this - input = [1,2,3,4] output = [1,4,9,16]
Ans. 
Code to square each element in the input array.
• Iterate through the input array and square each element.

• Store the squared values in a new array to get the desired output.
Answered by AI
Add your answer
Q5. Dataflow vs dataproc.
Ans. 
Dataflow is a fully managed stream and batch processing service, while Dataproc is a managed Apache Spark and Hadoop service.
• Dataflow is a serverless data processing service that automatically scales to handle your data, while Dataproc is a managed Spark and Hadoop service that requires you to provision and manage clusters.

• Dataflow is designed for both batch and stream processing, allowing you to process data in real-t...read more
Answered by AI
Add your answer
Q6. Architecture of bq. Query optimization techniques in bigquery.
Ans. 
BigQuery architecture includes storage, execution, and optimization components for efficient query processing.
• BigQuery stores data in Capacitor storage system for fast access.

• Query execution is distributed across multiple nodes for parallel processing.

• Query optimization techniques include partitioning tables, clustering tables, and using query cache.

• Using partitioned tables can help eliminate scanning unnecessary data.

• ...read more
Answered by AI
Add your answer
Q7. RDD vs dataframe vs dataset in pyspark
Ans. 
RDD vs dataframe vs dataset in PySpark
• RDD (Resilient Distributed Dataset) is the basic abstraction in PySpark, representing a distributed collection of objects

• Dataframe is a distributed collection of data organized into named columns, similar to a table in a relational database

• Dataset is a distributed collection of data with the ability to use custom classes for type safety and user-defined functions

• Dataframes and Data...read more
Answered by AI
Add your answer

Q1. Explain adf questions in detail
Ans. 
ADF questions refer to Azure Data Factory questions which are related to data integration and data transformation processes.
• ADF questions are related to Azure Data Factory, a cloud-based data integration service.

• These questions may involve data pipelines, data flows, activities, triggers, and data movement.

• Candidates may be asked about their experience with designing, monitoring, and managing data pipelines in ADF.

• Exam...read more
Answered by AI
Add your answer
Q2. Project related questions
Add your answer

Q1. Project data related questions
Add your answer
Q2. Databricks and SQL interview questions
Add your answer

Q1. What are the optimization techniques used in Apache Spark?
Add your answer
Q2. 2 SQL queries , 1 PySpark code and 1 Python Code .
Add your answer
Q3. 2-3 Scenario Based questions from ADF and databricks .
Add your answer

Q1. Difference between rank and dense_rank, Left vs Left anti join
Ans. 
Rank assigns unique ranks to rows, while dense_rank handles ties by assigning the same rank to tied rows. Left join includes all rows from the left table and matching rows from the right table, while left anti join includes only rows from the left table that do not have a match in the right table.
• Rank assigns unique ranks to rows based on the specified order, while dense_rank handles ties by assigning the same rank to ...read more
Answered by AI
Add your answer
Q2. Python list comprehension, SQL query
Add your answer

Q1. Project related questions
Add your answer

Aptitude test involved with quantative aptitude, logical reasoning and reading comprehensions.

Q1. Tell me your introduction.
Add your answer
Q2. Tell me about your skills.
Ans. 
I have strong skills in data processing, ETL, data modeling, and programming languages like Python and SQL.
• Proficient in data processing and ETL techniques

• Strong knowledge of data modeling and database design

• Experience with programming languages like Python and SQL

• Familiarity with big data technologies such as Hadoop and Spark
Answered by AI
Add your answer

Q1. Are you ready relocate,?
Ans. 
Yes, I am open to relocating for the right opportunity.
• I am willing to relocate for the right job opportunity.

• I have experience moving for previous roles.

• I am flexible and adaptable to new locations.

• I am excited about the possibility of exploring a new city or country.
Answered by AI
Add your answer
Q2. Document verification
Add your answer

Q1. About python, sql, pyspark
Add your answer
Q2. Spark Architecture.
Add your answer

Q1. When can you join.
Ans. 
I can join within two weeks of receiving an offer.
• I can start within two weeks of receiving an offer.

• I need to give notice at my current job before starting.

• I have some personal commitments that I need to wrap up before joining.
Answered by AI
Add your answer
Q2. .
Add your answer

Q1. General Data Warehousing questions like explain your pipeline, how you implemented scd2?
Add your answer
Q2. SQL questions like increment top 5th salary by 10k, last day of month, etc.
Add your answer