Professional Data Engineer Free Practice Questions — Page 13
Question 103
You orchestrate ETL pipelines by using Cloud Composer. One of the tasks in the Apache Airflow directed acyclic graph (DAG) relies on a third-party service. You want to be notified when the task does not succeed. What should you do?
A. Assign a function with notification logic to the on_retry_callback parameter for the operator responsible for the task at risk.
B. Configure a Cloud Monitoring alert on the sla_missed metric associated with the task at risk to trigger a notification.
C. Assign a function with notification logic to the on_failure_callback parameter tor the operator responsible for the task at risk.
D. Assign a function with notification logic to the sla_miss_callback parameter for the operator responsible for the task at risk.
Show Answer
Correct Answer: C
Explanation: In Apache Airflow, the on_failure_callback is explicitly invoked when a task fails. Attaching a notification function to this callback ensures you are alerted whenever the task relying on the third-party service does not succeed. Other options handle retries, SLA misses, or indirect monitoring rather than direct task failure.
Question 104
You have a Cloud SQL for PostgreSQL instance in Region’ with one read replica in Region2 and another read replica in Region3. An unexpected event in Region’ requires that you perform disaster recovery by promoting a read replica in Region2. You need to ensure that your application has the same database capacity available before you switch over the connections. What should you do?
A. Enable zonal high availability on the primary instance. Create a new read replica in a new region.
B. Create a cascading read replica from the existing read replica in Region3.
C. Create two new read replicas from the new primary instance, one in Region3 and one in a new region.
D. Create a new read replica in Region1, promote the new read replica to be the primary instance, and enable zonal high availability.
Show Answer
Correct Answer: C
Explanation: After promoting the read replica in Region2 to become the new primary, the original primary and its replication topology are no longer usable. To ensure the same database capacity (one primary plus two read replicas) before switching application traffic, you must recreate read replicas from the new primary. Creating two new read replicas—one in Region3 (replacing the unusable existing replica) and one in another region—restores the original read capacity and geographic redundancy.
Question 105
You have a BigQuery table that contains customer data, including sensitive information such as names and addresses. You need to share the customer data with your data analytics and consumer support teams securely. The data analytics team needs to access the data of all the customers, but must not be able to access the sensitive data. The consumer support team needs access to all data columns, but must not be able to access customers that no longer have active contracts. You enforced these requirements by using an authorized dataset and policy tags. After implementing these steps, the data analytics team reports that they still have access to the sensitive columns. You need to ensure that the data analytics team does not have access to restricted data. What should you do? (Choose two.)
A. Create two separate authorized datasets; one for the data analytics team and another for the consumer support team.
B. Ensure that the data analytics team members do not have the Data Catalog Fine-Grained Reader role for the policy tags.
C. Replace the authorized dataset with an authorized view. Use row-level security and apply filter_expression to limit data access.
D. Remove the bigquery.dataViewer role from the data analytics team on the authorized datasets.
E. Enforce access control in the policy tag taxonomy.
Show Answer
Correct Answer: B, E
Explanation: BigQuery column-level security with policy tags is enforced through the policy tag taxonomy. If the data analytics team can still see sensitive columns, they have access to the relevant policy tags. You must ensure they are not granted the Data Catalog Fine-Grained Reader (or higher) role on those policy tags (B) and correctly enforce access control in the policy tag taxonomy by granting tag access only to authorized users (E). Other options either remove all access, address row-level security, or add unnecessary complexity.
Question 106
You are developing an Apache Beam pipeline to extract data from a Cloud SQL instance by using JdbcIO. You have two projects running in Google Cloud. The pipeline will be deployed and executed on Dataflow in Project A. The Cloud SQL. instance is running in Project B and does not have a public IP address. After deploying the pipeline, you noticed that the pipeline failed to extract data from the Cloud SQL instance due to connection failure. You verified that VPC Service Controls and shared VPC are not in use in these projects. You want to resolve this error while ensuring that the data does not go through the public internet. What should you do?
A. Set up VPC Network Peering between Project A and Project B. Add a firewall rule to allow the peered subnet range to access all instances on the network.
B. Turn off the external IP addresses on the Dataflow worker. Enable Cloud NAT in Project A.
C. Add the external IP addresses of the Dataflow worker as authorized networks in the Cloud SQL instance.
D. Set up VPC Network Peering between Project A and Project B. Create a Compute Engine instance without external IP address in Project B on the peered subnet to serve as a proxy server to the Cloud SQL database.
Show Answer
Correct Answer: A
Explanation: Cloud SQL uses a private IP and resides in Project B, while Dataflow workers run in Project A. To keep traffic off the public internet, the two VPC networks must have private connectivity. VPC Network Peering enables direct private IP communication between the projects, allowing Dataflow workers to reach the Cloud SQL private IP without a proxy or public IPs. A proxy VM (option D) is unnecessary overhead, Cloud NAT does not help for inbound connections to Cloud SQL, and authorizing external IPs would require public internet access.
Question 107
You are administering a BigQuery dataset that uses a customer-managed encryption key (CMEK). You need to share the dataset with a partner organization that does not have access to your CMEK. What should you do?
A. Provide the partner organization a copy of your CMEKs to decrypt the data.
B. Export the tables to parquet files to a Cloud Storage bucket and grant the storageinsights.viewer role on the bucket to the partner organization.
C. Copy the tables you need to share to a dataset without CMEKs. Create an Analytics Hub listing for this dataset.
D. Create an authorized view that contains the CMEK to decrypt the data when accessed.
Show Answer
Correct Answer: C
Explanation: BigQuery datasets encrypted with a customer-managed encryption key require any reader to have access to that key. Since the partner organization does not have CMEK access, you must avoid sharing CMEK-protected data directly. The correct approach is to copy the required tables into a dataset that uses Google-managed encryption (no CMEK) and then share that dataset. Using Analytics Hub is the recommended, secure, and governed way to share BigQuery datasets across organizations without exposing encryption keys.
Question 108
You have a Standard Tier Memorystore for Redis instance deployed in a production environment. You need to simulate a Redis instance failover in the most accurate disaster recovery situation, and ensure that the failover has no impact on production data. What should you do?
A. Create a Standard Tier Memorystore for Redis instance in the development environment. Initiate a manual failover by using the limited-data-loss data protection mode.
B. Create a Standard Tier Memorystore for Redis instance in a development environment. Initiate a manual failover by using the force-data-loss data protection mode.
C. Increase one replica to Redis instance in production environment. Initiate a manual failover by using the force-data-loss data protection mode.
D. Initiate a manual failover by using the limited-data-loss data protection mode to the Memorystore for Redis instance in the production environment.
Show Answer
Correct Answer: B
Explanation: The requirement is to simulate failover as accurately as possible while ensuring no impact on production data. Any failover performed on the production instance (options C and D) inherently risks data loss or service disruption. Therefore, the simulation must be done in a separate development environment. To most accurately test disaster recovery, the force-data-loss data protection mode should be used, as it aggressively executes failover and best simulates severe failure scenarios. Limited-data-loss mode is safer but does not fully stress disaster recovery behavior. Hence, option B is the best choice.
Question 109
Your company's customer_order table in BigQuery stores the order history for 10 million customers, with a table size of 10 PB. You need to create a dashboard for the support team to view the order history. The dashboard has two filters, country_name and username. Both are string data types in the BigQuery table. When a filter is applied, the dashboard fetches the order history from the table and displays the query results. However, the dashboard is slow to show the results when applying the filters to the following query:
How should you redesign the BigQuery table to support faster access?
A. Cluster the table by country and username fields.
B. Cluster the table by country field, and partition by username field.
C. Partition the table by country and username fields.
D. Partition the table by _PARTITIONTIME.
Show Answer
Correct Answer: A
Explanation: The dashboard filters on country_name and username, both string columns. BigQuery partitioning does not support arbitrary string columns (except limited integer-range or time-based partitioning), and partitioning by username would also exceed partition limits due to very high cardinality. Clustering is designed for exactly this use case: it physically organizes data by the filtered columns so that queries scan far less data. Clustering by both country and username directly optimizes the filter predicates and provides the fastest access without inappropriate or ineffective partitioning.
Question 110
You are troubleshooting your Dataflow pipeline that processes data from Cloud Storage to BigQuery. You have discovered that the Dataflow worker nodes cannot communicate with one another. Your networking team relies on Google Cloud network tags to define firewall rules. You need to identify the issue while following Google-recommended networking security practices. What should you do?
A. Determine whether your Dataflow pipeline has a custom network tag set.
B. Determine whether there is a firewall rule set to allow traffic on TCP ports 12345 and 12346 for the Dataflow network tag.
C. Determine whether there is a firewall rule set to allow traffic on TCP ports 12345 and 12346 on the subnet used by Dataflow workers.
D. Determine whether your Dataflow pipeline is deployed with the external IP address option enabled.
Show Answer
Correct Answer: B
Explanation: Dataflow worker-to-worker communication requires specific TCP ports (12345 and 12346). Google-recommended practice is to control such access using firewall rules based on network tags rather than subnets or external IPs. Since the networking team relies on network tags, the correct troubleshooting step is to verify that a firewall rule exists allowing traffic on these ports for the Dataflow network tag. Without this rule, workers cannot communicate.
Question 111
You are using BigQuery with a multi-region dataset that includes a table with the daily sales volumes. This table is updated multiple times per day. You need to protect your sales table in case of regional failures with a recovery point objective (RPO) of less than 24 hours, while keeping costs to a minimum. What should you do?
A. Schedule a daily export of the table to a Cloud Storage dual or multi-region bucket.
B. Schedule a daily copy of the dataset to a backup region.
C. Schedule a daily BigQuery snapshot of the table.
D. Modify ETL job to load the data into both the current and another backup region.
Show Answer
Correct Answer: A
Explanation: The requirement is protection against a regional failure with an RPO < 24 hours at minimal cost. BigQuery table snapshots (C) are stored in the same region as the source table and do not increase durability against regional loss. Copying datasets to another region (B) or dual-writing via ETL (D) provides protection but is more expensive and operationally complex. Exporting the table daily to a Cloud Storage dual- or multi-region bucket places the backup in a geographically distinct location, satisfies the RPO, and is the most cost-effective disaster recovery approach recommended by BigQuery reliability guidance.
Question 112
You are designing a data mesh on Google Cloud with multiple distinct data engineering teams building data products. The typical data curation design pattern consists of landing files in Cloud Storage, transforming raw data in Cloud Storage and BigQuery datasets, and storing the final curated data product in BigQuery datasets. You need to configure Dataplex to ensure that each team can access only the assets needed to build their data products. You also need to ensure that teams can easily share the curated data product. What should you do?
A. 1. Create a single Dataplex virtual lake and create a single zone to contain landing, raw, and curated data. 2. Provide each data engineering team access to the virtual lake.
B. 1. Create a single Dataplex virtual lake and create a single zone to contain landing, raw, and curated data. 2. Build separate assets for each data product within the zone. 3. Assign permissions to the data engineering teams at the zone level.
C. 1. Create a Dataplex virtual lake for each data product, and create a single zone to contain landing, raw, and curated data. 2. Provide the data engineering teams with full access to the virtual lake assigned to their data product.
D. 1. Create a Dataplex virtual lake for each data product, and create multiple zones for landing, raw, and curated data. 2. Provide the data engineering teams with full access to the virtual lake assigned to their data product.
Show Answer
Correct Answer: D
Explanation: Dataplex best practice for a data mesh is to model each data product (domain) as its own virtual lake, with zones separating stages such as landing, raw, and curated. This gives strong isolation so each team can access only the assets needed to build their product, while zones enforce stage-level governance. Curated zones can then be shared across lakes to enable easy consumption of finalized data products by other teams. Options with a single lake or single zone do not provide sufficient isolation or follow Dataplex design patterns.
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