Google Cloud Data Services Questions

Covers design and operational knowledge of Google Cloud Platform data products used for storage, processing, streaming, and analytics. Key skills include when and how to use BigQuery for serverless analytics and data warehousing, Dataflow for stream and batch pipelines built on Apache Beam, Cloud Storage for object store and data lake patterns, and Pub/Sub for messaging and event ingestion. Candidates should understand cost models, performance trade offs, schema and partitioning strategies, data ingestion and export patterns, pipeline monitoring and error handling, and integration between these services for end to end data solutions.

MediumSystem Design

94 practiced

Design a data ingestion and processing pipeline that can sustain 100,000 events per second (≈1 KB per event) and deliver transformed records into BigQuery within 60 seconds of arrival. Outline Pub/Sub topic/subscription strategy, Dataflow scaling and batching, BigQuery write approach, partitioning and cost trade-offs.

MediumTechnical

89 practiced

Given three client requirements, recommend the most suitable Google data product and justify your choices: (1) high-throughput time-series storage with low-latency point reads, (2) petabyte-scale analytical reporting, (3) globally-distributed transactional customer data with strong consistency.

HardSystem Design

80 practiced

Describe a robust approach to build end-to-end data lineage across Pub/Sub topics, Dataflow transforms, Cloud Storage objects, and BigQuery tables so auditors can trace a value from ingestion to report. Include how to instrument pipelines, where to store lineage metadata, and how consumers can query lineage.

MediumTechnical

99 practiced

You receive continuous time-series sensor data. Propose a BigQuery table schema and partitioning/clustering strategy to support queries for hourly aggregates, recent N-day queries, and device-level metrics. Explain your choices and expected query performance characteristics.

EasyTechnical

92 practiced

Explain Cloud Pub/Sub's core concepts (topics, subscriptions, messages) and its default delivery semantics. Summarize delivery guarantees, ack-deadline behavior, and briefly when you would prefer Pub/Sub Lite over standard Pub/Sub.

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