PDE Maintaining and Automating Data Workloads Practice Question
A data engineer uses Cloud Composer to orchestrate a daily batch pipeline. A downstream task should only start after an upstream BigQuery load job finishes successfully and a specific file appears in Cloud Storage. Which combination of operators should the engineer use in the Airflow DAG?
⚠ Common exam trap
The trap is assuming that a single operator can handle both conditions or that wait_for_downstream covers external dependencies; candidates must recognize the need for a separate sensor and correct dependency direction.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
BigQueryInsertJobOperator and GCSObjectExistenceSensor with upstream dependency
The engineer needs a BigQuery load job to finish successfully and a specific file to appear in Cloud Storage before a downstream task starts. The correct combination is BigQueryInsertJobOperator to run and wait for the BigQuery job, and GCSObjectExistenceSensor to check for the file, with the sensor set as an upstream dependency of the downstream task. This ensures both conditions are met before proceeding.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
BigQueryInsertJobOperator with wait_for_downstream=True
Why it's wrong here
wait_for_downstream delays the task until its downstream tasks finish, which is the opposite of gating a downstream task on this job's success. It would suit ensuring cleanup completes before a task reruns, not sequencing a BigQuery load before a sensor.
- ✓
BigQueryInsertJobOperator and GCSObjectExistenceSensor with upstream dependency
Why this is correct
BigQueryInsertJobOperator runs the load job, while GCSObjectExistenceSensor pokes Cloud Storage until the file appears. Setting the sensor as an upstream dependency forces the downstream task to wait for both the successful load and the file's arrival, satisfying the dual trigger condition.
- ✗
DataflowPythonOperator and GCSObjectExistenceSensor
Why it's wrong here
DataflowPythonOperator launches a Dataflow job, not a BigQuery load, so the upstream success condition is never satisfied. It would be right if the pipeline ran Apache Beam transforms on Dataflow; the stem requires a BigQuery load operator plus a Cloud Storage sensor.
- ✗
BigQueryOperator and FileSensor with downstream dependency
Why it's wrong here
FileSensor polls the local filesystem or a path visible to the worker, not Cloud Storage objects, so the file-appearance condition fails. It would be correct for files on a mounted volume; the stem needs GCSObjectExistenceSensor to detect the Cloud Storage object.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PDE exam.