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Google Data Engineer Sample Questions:

1. You are integrating one of your internal IT applications and Google BigQuery, so users can query BigQuery from the application's interface. You do not want individual users to authenticate to BigQuery and you do not want to give them access to the dataset. You need to securely access BigQuery from your IT application.
What should you do?

A) Create groups for your users and give those groups access to the dataset
B) Use the service account's private key to access the dataset
C) Integrate with a single sign-on (SSO) platform, and pass each user's credentials along with the query request
D) Create a service account and grant dataset access to that accoun
E) Create a dummy user and grant dataset access to that use
F) Store the username and password for that user in a file on the files system, and use those credentials to access the BigQuery dataset

2. Which of the following statements is NOT true regarding Bigtable access roles?

A) You can configure access control only at the project level.
B) Using IAM roles, you cannot give a user access to only one table in a project, rather than all tables in a project.
C) To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.
D) To give a user access to only one table in a project, you must configure access through your application.

3. You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

A) Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
B) Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
C) Deploy the Cloud SQL Proxy on the Cloud Dataproc master
D) Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet

4. As your organization expands its usage of GCP, many teams have started to create their own projects. Projects are further multiplied to accommodate different stages of deployments and target audiences. Each project requires unique access control configurations. The central IT team needs to have access to all projects. Furthermore, data from Cloud Storage buckets and BigQuery datasets must be shared for use in other projects in an ad hoc way. You want to simplify access control management by minimizing the number of policies. Which two steps should you take? Choose 2 answers.

A) Use Cloud Deployment Manager to automate access provision.
B) Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.
C) Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.
D) For each Cloud Storage bucket or BigQuery dataset, decide which projects need acces
E) Create distinct groups for various teams, and specify groups in Cloud IAM policies.
F) Introduce resource hierarchy to leverage access control policy inheritance.

5. You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

A) Workflow Templates on Cloud Dataproc
B) cron
C) Cloud Composer
D) Cloud Scheduler

Solutions: