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Google Data Engineer Sample Questions:

1. Which of the following is NOT true about Dataflow pipelines?

A) Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources
B) Dataflow pipelines can be programmed in Java
C) Dataflow pipelines can consume data from other Google Cloud services
D) Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner

2. You are responsible for writing your company's ETL pipelines to run on an Apache Hadoop cluster. The pipeline will require some checkpointing and splitting pipelines. Which method should you use to write the pipelines?

A) Java using MapReduce
B) HiveQL using Hive
C) PigLatin using Pig
D) Python using MapReduce

3. You receive data files in CSV format monthly from a third party. You need to cleanse this data, but every third month the schema of the files changes. Your requirements for implementing these transformations include:
Executing the transformations on a schedule
Enabling non-developer analysts to modify transformations
Providing a graphical tool for designing transformations
What should you do?

A) Help the analysts write a Cloud Dataflow pipeline in Python to perform the transformatio
B) Load each month's CSV data into BigQuery, and write a SQL query to transform the data to a standard scheme
C) The Python code should be stored in a revision control system and modified as the incoming data's schema changes
D) Use Cloud Dataprep to build and maintain the transformation recipes, and execute them on a scheduled basis
E) Use Apache Spark on Cloud Dataproc to infer the schema of the CSV file before creating a Dataframe.Then implement the transformations in Spark SQL before writing the data out to Cloud Storage and loading into BigQuery
F) Merge the transformed tables together with a SQL query

4. Which is not a valid reason for poor Cloud Bigtable performance?

A) The workload isn't appropriate for Cloud Bigtable.
B) The Cloud Bigtable cluster has too many nodes.
C) There are issues with the network connection.
D) The table's schema is not designed correctly.

5. You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?

A) Create an authorized view in BigQuery to restrict access to tables with sensitive data.
B) Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
C) Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.
D) Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention AP
E) Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.

Solutions: