10+ Gcp Data Engineer Interview Questions and Answers for Freshers

Real-time data services can be used to migrate datawarehouse with GCP services.

• Use Cloud Dataflow to ingest and transform data in real-time

• Use Cloud Pub/Sub to stream data to BigQuery or Cloud Storage

• Use Cloud Dataproc to process data in real-time

• Use Cloud Composer to orchestrate data pipelines

• Use Cloud Spanner for real-time transactional data

• Use Cloud SQL for real-time relational data

• Use Cloud Bigtable for real-time NoSQL data

Data pipelines in GCP can be created using various tools like Dataflow, Dataproc, and Cloud Composer.

• Choose the appropriate tool based on the use case and data volume

• Define the data source and destination

• Create a pipeline using the chosen tool and define the data transformations

• Test and deploy the pipeline

• Monitor and troubleshoot the pipeline for any issues

I have used various services in GCP including BigQuery, Dataflow, Cloud Storage, and Pub/Sub.

• BigQuery for data warehousing and analytics

• Dataflow for data processing and ETL

• Cloud Storage for storing and accessing data

• Pub/Sub for messaging and event-driven architectures

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

Types of NoSQL databases in GCP include Firestore, Bigtable, and Datastore.

• Firestore is a flexible, scalable database for mobile, web, and server development.

• Bigtable is a high-performance NoSQL database service for large analytical and operational workloads.

• Datastore is a highly scalable NoSQL database for web and mobile applications.

Window functions in BigQuery are used to perform calculations across a set of table rows related to the current row.

• Window functions allow you to perform calculations on a set of rows related to the current row

• They are used with the OVER() clause in SQL queries

• Common window functions include ROW_NUMBER(), RANK(), and NTILE()

• They can be used to calculate moving averages, cumulative sums, and more

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

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

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