I have assembled some links for the exam, broken down by section. These links were from the A Cloud Guru practice exam explanations.

Section 1. Designing data processing systems
https://cloud.google.com/bigquery/docs
https://cloud.google.com/pubsub/docs/ordering
https://cloud.google.com/dataproc/docs/guides/dataproc-images
https://cloud.google.com/bigquery/docs/loading-data-cloud-storage-json
https://beam.apache.org/documentation/programming-guide/#core-beam-transforms
https://cloud.google.com/spanner/docs/secondary-indexes
https://cloud.google.com/spanner/docs/true-time-external-consistency
https://cloud.google.com/dataproc/docs
https://cloud.google.com/storage/docs/storage-classes
https://cloud.google.com/bigtable/docs/overview
https://cloud.google.com/bigquery/docs/loading-data-cloud-storage-avro
https://cloud.google.com/bigtable/docs
https://cloud.google.com/dataflow/docs
https://cloud.google.com/bigtable/docs/concepts
https://cloud.google.com/datastore/docs/concepts/overview
https://beam.apache.org/documentation/programming-guide/#side-inputs
https://cloud.google.com/dataproc/docs/guides/dataproc-images
https://cloud.google.com/solutions/migration/hadoop/migrating-apache-spark-jobs-to-cloud-dataproc
https://cloud.google.com/iam/docs/understanding-service-accounts
https://cloud.google.com/bigquery/docs/loading-data-cloud-storage-json
Section 2. Building and operationalizing data processing systems
https://cloud.google.com/pubsub/docs
https://beam.apache.org/documentation/programming-guide/#core-beam-transforms
https://cloud.google.com/bigtable/docs/schema-design-time-series#patterns_for_row_key_design
https://cloud.google.com/dataflow/docs/guides/deploying-a-pipeline
https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/autoscaling
https://cloud.google.com/pubsub/docs/replay-overview
https://cloud.google.com/pubsub/docs/monitoring
https://cloud.google.com/transfer-appliance/docs/2.0
https://cloud.google.com/bigquery/docs
https://cloud.google.com/bigtable/docs/overview
https://cloud.google.com/bigquery/docs/share-access-views
https://cloud.google.com/blog/products/gcp/handling-invalid-inputs-in-dataflow
https://beam.apache.org/documentation/runners/direct/
https://cloud.google.com/dataflow/docs
https://cloud.google.com/bigtable/docs/performance
https://cloud.google.com/bigquery/docs/partitioned-tables#date_timestamp_partitioned_tables
https://cloud.google.com/bi-engine/docs/getting-started-data-studio
Section 3. Operationalizing machine learning models
https://cloud.google.com/ai-platform/deep-learning-vm/docs
https://cloud.google.com/vision/automl/docs
https://cloud.google.com/ai-platform/docs/ml-solutions-overview
https://cloud.google.com/ai-platform/docs
https://cloud.google.com/vision/automl/docs/predict-batch
https://cloud.google.com/natural-language/automl/docs/prepare#classification
https://developers.google.com/machine-learning/crash-course/descending-into-ml/linear-regression
https://cloud.google.com/speech-to-text/docs
Section 4. Ensuring solution quality
https://cloud.google.com/datalab/docs
https://cloud.google.com/bigquery/docs
https://cloud.google.com/bigtable/docs/overview
https://cloud.google.com/bigtable/quotas#storage-per-node
https://cloud.google.com/sql/docs/mysql/maintenance
https://cloud.google.com/billing/docs/how-to/billing-access
https://support.google.com/datastudio/answer/7020039?hl=en
https://cloud.google.com/storage/docs/lifecycle
https://cloud.google.com/bigquery/docs/table-access-controls-intro
https://cloud.google.com/bigtable/docs/overview
https://cloud.google.com/bigquery/docs/visualize-data-studio
https://cloud.google.com/storage/docs/access-control/signed-urls
I don’t purport for these lists to be exhaustive. Use the lists as a starting point.
As of this time, I will be writing the GCP Data Engineer exam in 3 days. I will go over my exam preparation in the next few weeks.
