Bornemindz Software Solutions Gcp Data Engineer Interview Questions and Answers

I have experience working on projects involving data processing, transformation, and analysis using GCP services like BigQuery, Dataflow, and Dataproc.

• Utilized BigQuery for storing and querying large datasets

• Implemented data pipelines using Dataflow for real-time data processing

• Utilized Dataproc for running Apache Spark and Hadoop clusters for data processing

• Worked on data ingestion and transformation using Cloud Stora

IAM is Identity and Access Management, SA is Service Account, BigQuery is a data warehouse, QlikSense is a data visualization tool, GitHub is a version control system, Spark is a distributed computing framework, Airflow is a workflow automation tool, Bigtable is a NoSQL database, Cloud Composer is a managed workflow orchestration service, Pub/Sub is a messaging service.

• IAM is used to manage access to resources in Googl...read more

Check if a string is a palindrome or not

• Compare the string with its reverse to check for palindrome

• Ignore spaces and punctuation marks when comparing

• Examples: 'racecar' is a palindrome, 'hello' is not

Use Python to create a GCS bucket

• Import the necessary libraries like google.cloud.storage

• Authenticate using service account credentials

• Use the library functions to create a new bucket

Python code to trigger a dataflow job in cloud function

• Use the googleapiclient library to interact with the Dataflow API

• Authenticate using service account credentials

• Submit a job to Dataflow using the projects.locations.templates.launch endpoint

Use SQL to find keys present in table A but not in table B (old copy of A).

• Use a LEFT JOIN to combine tables A and B based on the key column

• Filter the results where the key column in table B is NULL

• This will give you the keys present in table A but not in table B

Use GCP Dataflow to transfer files between GCS buckets

• Create a Dataflow pipeline using Apache Beam to read from source bucket and write to destination bucket

• Use GCS connector to read and write files in Dataflow pipeline

• Set up appropriate permissions for Dataflow service account to access both buckets

Cloud Composer is another orchestration tool in GCP

• Cloud Composer is a fully managed workflow orchestration service built on Apache Airflow

• It allows you to author, schedule, and monitor workflows that span across GCP services

• Cloud Composer provides a rich set of features like DAGs, plugins, and monitoring capabilities

• It integrates seamlessly with other GCP services like BigQuery, Dataflow, and Dataproc

BigQuery is used for analyzing large datasets and running complex queries, while SQL is used for querying databases.

• BigQuery is used for analyzing large datasets quickly and efficiently

• SQL is used for querying databases to retrieve specific data

• BigQuery can handle petabytes of data, making it ideal for big data analysis

• SQL can be used to perform operations like filtering, sorting, and aggregating data

SQL joins are used to combine rows from two or more tables based on a related column between them.

• SQL joins are used to retrieve data from multiple tables based on a related column between them

• Types of SQL joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN

• In BigQuery, joins can be performed using standard SQL syntax

• Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column