S
Google Professional Data Engineer (PDE) ACTUAL
PRACTICE EXAM 2026/2027 | Verified Questions
and Answers | Complex Architectural Scenarios &
Trade-off Analysis | Exam Pass Target - A+ Graded
Section 1: Designing Data Processing Systems (Questions 1-15)
Q1: A retail company needs to store and analyze 50 TB of sales transaction data with the
following requirements: sub-second query latency for dashboards, support for standard SQL, and
automatic scaling. Data is append-only with no updates. Current daily ingestion is 100 GB.
Which storage solution is most cost-effective and performant?
A. Cloud SQL with read replicas for query performance B. BigQuery with partitioned tables and
appropriate clustering [CORRECT] C. Cloud Bigtable with column families optimized for time-
series data D. Cloud Storage with Avro files queried via Dataproc
Correct Answer: B
Q2: A gaming company needs to store player session data with the following characteristics:
millions of rows per second ingestion, millisecond-latency reads by player ID, data expires after
30 days, and schema is flexible (different games store different attributes). Which solution meets
all requirements?
A. BigQuery with streaming inserts B. Cloud Bigtable with time-to-live (TTL) and column
families [CORRECT] C. Cloud SQL with sharding D. Firestore with automatic scaling
Correct Answer: B
Q3: A financial services firm must store sensitive customer transaction data for 7 years to meet
regulatory requirements. Data is rarely accessed after 90 days but must be retained. They need
strong encryption and audit logging. Which approach optimizes cost while meeting compliance?
A. Store all data in BigQuery with CMEK B. Use Cloud Storage with lifecycle policies to move
data to Archive storage class after 90 days, with CMEK and Access Transparency logs
[CORRECT] C. Keep all data in Cloud SQL with automatic backups D. Use Persistent Disk
snapshots with custom encryption
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Correct Answer: B
Q4: A company needs to design a data pipeline for processing clickstream data. Requirements:
process 100,000 events/second, exactly-once semantics, transform data with complex business
logic, and write to BigQuery and Cloud Storage. Which architecture is optimal?
A. Cloud Pub/Sub → Dataflow (Apache Beam) → BigQuery and Cloud Storage [CORRECT] B.
Cloud Pub/Sub → Cloud Functions → BigQuery C. Cloud Logging → BigQuery directly D.
Cloud Storage → Dataproc batch jobs → BigQuery
Correct Answer: A
Q5: An e-commerce platform needs to migrate a PostgreSQL database to GCP with minimal
downtime. The database is 2 TB with heavy write activity. They need a managed solution that
supports complex joins and ACID transactions. Which approach is best?
A. Migrate to Cloud Spanner for global consistency B. Use Database Migration Service to
migrate to Cloud SQL for PostgreSQL with read replicas [CORRECT] C. Migrate to BigQuery
and rewrite applications D. Use Firestore with Datastore mode
Correct Answer: B
Q6: A data architect is designing storage for a machine learning feature store. Requirements:
low-latency serving (<10ms), high throughput for batch writes, support for vector similarity
search, and integration with Vertex AI. Which solution is most appropriate?
A. BigQuery with BI Engine B. Vertex AI Feature Store or Bigtable with appropriate indexing
[CORRECT] C. Cloud SQL with custom indexes D. Cloud Storage with TensorFlow I/O
Correct Answer: B
Q7: A company needs to store and query JSON documents with nested structures. Queries filter
on multiple fields with varying selectivity. Data volume is 500 GB and growing 10% monthly.
They need full SQL support and no operational overhead. Which service should they use?
A. Cloud Bigtable with JSON serialization B. BigQuery with native JSON and repeated fields
support [CORRECT] C. Cloud SQL with JSON columns D. Firestore with composite indexes
Correct Answer: B
Google Professional Data Engineer (PDE) ACTUAL
PRACTICE EXAM 2026/2027 | Verified Questions
and Answers | Complex Architectural Scenarios &
Trade-off Analysis | Exam Pass Target - A+ Graded
Section 1: Designing Data Processing Systems (Questions 1-15)
Q1: A retail company needs to store and analyze 50 TB of sales transaction data with the
following requirements: sub-second query latency for dashboards, support for standard SQL, and
automatic scaling. Data is append-only with no updates. Current daily ingestion is 100 GB.
Which storage solution is most cost-effective and performant?
A. Cloud SQL with read replicas for query performance B. BigQuery with partitioned tables and
appropriate clustering [CORRECT] C. Cloud Bigtable with column families optimized for time-
series data D. Cloud Storage with Avro files queried via Dataproc
Correct Answer: B
Q2: A gaming company needs to store player session data with the following characteristics:
millions of rows per second ingestion, millisecond-latency reads by player ID, data expires after
30 days, and schema is flexible (different games store different attributes). Which solution meets
all requirements?
A. BigQuery with streaming inserts B. Cloud Bigtable with time-to-live (TTL) and column
families [CORRECT] C. Cloud SQL with sharding D. Firestore with automatic scaling
Correct Answer: B
Q3: A financial services firm must store sensitive customer transaction data for 7 years to meet
regulatory requirements. Data is rarely accessed after 90 days but must be retained. They need
strong encryption and audit logging. Which approach optimizes cost while meeting compliance?
A. Store all data in BigQuery with CMEK B. Use Cloud Storage with lifecycle policies to move
data to Archive storage class after 90 days, with CMEK and Access Transparency logs
[CORRECT] C. Keep all data in Cloud SQL with automatic backups D. Use Persistent Disk
snapshots with custom encryption
, S
Correct Answer: B
Q4: A company needs to design a data pipeline for processing clickstream data. Requirements:
process 100,000 events/second, exactly-once semantics, transform data with complex business
logic, and write to BigQuery and Cloud Storage. Which architecture is optimal?
A. Cloud Pub/Sub → Dataflow (Apache Beam) → BigQuery and Cloud Storage [CORRECT] B.
Cloud Pub/Sub → Cloud Functions → BigQuery C. Cloud Logging → BigQuery directly D.
Cloud Storage → Dataproc batch jobs → BigQuery
Correct Answer: A
Q5: An e-commerce platform needs to migrate a PostgreSQL database to GCP with minimal
downtime. The database is 2 TB with heavy write activity. They need a managed solution that
supports complex joins and ACID transactions. Which approach is best?
A. Migrate to Cloud Spanner for global consistency B. Use Database Migration Service to
migrate to Cloud SQL for PostgreSQL with read replicas [CORRECT] C. Migrate to BigQuery
and rewrite applications D. Use Firestore with Datastore mode
Correct Answer: B
Q6: A data architect is designing storage for a machine learning feature store. Requirements:
low-latency serving (<10ms), high throughput for batch writes, support for vector similarity
search, and integration with Vertex AI. Which solution is most appropriate?
A. BigQuery with BI Engine B. Vertex AI Feature Store or Bigtable with appropriate indexing
[CORRECT] C. Cloud SQL with custom indexes D. Cloud Storage with TensorFlow I/O
Correct Answer: B
Q7: A company needs to store and query JSON documents with nested structures. Queries filter
on multiple fields with varying selectivity. Data volume is 500 GB and growing 10% monthly.
They need full SQL support and no operational overhead. Which service should they use?
A. Cloud Bigtable with JSON serialization B. BigQuery with native JSON and repeated fields
support [CORRECT] C. Cloud SQL with JSON columns D. Firestore with composite indexes
Correct Answer: B
