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Updated weekly · Last refresh Oct 17

Guardant Health Data Engineer Interview Questions

The questions to prepare for a Guardant Health Data Engineer interview. Questions from real interview reports rank first. Updated daily.

15questions
~2htotal time
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1
PipelinesStart here. 12 questions · ~106 min
Sustainable Secure Pipeline DesignMedium

Explain how to design pipelines that stay maintainable, secure, and aligned with engineering best practices over time.

InfrastructureData ModelingQualityGuardant Health
Structured vs Unstructured Pipeline DataEasy

Explain how structured and unstructured data differ, and how that changes pipeline design and downstream modeling.

InfrastructureData ModelingQualityGuardant Health
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityGuardant Health
Data Modeling TechniquesMedium

Tests your modeling choices for analytics, lineage, and maintainability.

InfrastructureETLData ModelingGuardant Health
Building a Data PipelineMedium

Tests your hands-on pipeline implementation experience from ingestion through transformation and delivery.

ToolsETLBatch ProcessingGuardant Health
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2
SQL & Data Manipulation3 questions + 2 drills · ~46 min
Optimizing Slow SQL QueriesMedium

Tests your SQL performance troubleshooting and optimization approach.

Window FunctionsJoinsAggregationsGuardant Health
Deduplicating Data in SQL and PySparkMedium

Evaluates your ability to implement and verify deduplication in SQL and PySpark.

pysparksqlGuardant Health
Optimize SQL Query PerformanceHard
Practice

Optimize a PostgreSQL reporting query by reducing intermediate rows, using appropriate joins, and calculating monthly performance efficiently.

database optimizationdatabase managementindexesGuardant Health
Monthly Sales Trends by CategoryMedium
Practice
Practice drill

Aggregate monthly sales by product category and use LAG to calculate month-over-month changes.

InfrastructureToolsData WranglingTotal Wine & MoreInc.Benjamin Moore
Contact Center Agent Performance MetricsHard
Practice
Practice drill

Compute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.

ETLAggregationsData ModelingADP

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