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Updated weekly · Last refresh Aug 30

Randstad Data Engineer Interview Questions

The questions to prepare for a Randstad Data Engineer interview. Questions from real interview reports rank first. Updated weekly.

13questions
~2htotal time
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1
PipelinesStart here. 6 questions · ~48 min
Data Quality and Schema EvolutionMedium

Approach for handling schema changes and data quality checks in a high-volume data lake pipeline.

schema evolutionData ModelingQualityRandstad
Testing and CI for PipelinesEasy

Explain how you apply automated testing and CI practices to data pipelines and pipeline releases.

InfrastructureToolsQualityRandstad
High-Concurrency Data Warehouse DesignMedium

Evaluates your ability to design for performance under concurrent reporting workloads.

data warehouseRandstad
Schema for Global Talent DatabaseHard

Tests your ability to model data for scalable, high-throughput reads and writes.

schema designperformancedatabaseRandstad
Azure Data Factory vs SynapseMedium

Assesses your understanding of Azure data services and when to apply each.

Use CasesRandstad
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2
Behavioral & Leadership5 questions · ~40 min
Mentoring a Junior EngineerEasy

Tests how effectively you mentor junior engineers through structured coaching, clear expectations, and measurable growth.

MentorshipCommunicationLeadershipRandstad
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3
More topics2 questions · ~16 min
API Basics and OptimizationMedium

Assesses your fundamentals of APIs and your ability to improve performance and reliability.

apioptimizationRandstad
Optimizing PySpark PerformanceMedium

Tests your ability to diagnose and improve Spark job performance.

pysparkdata processingperformance optimizationRandstad

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
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
Resolve Conflicting Customer AttributesMedium
Practice
Practice drill

Use joins, CTEs, and row ranking to resolve conflicting customer profile values across ACME House systems.

JoinsData WranglingQualityRamsey SolutionsACME House
The finish line: interview-readyComplete all 13 questions plus 3 hands-on drills to finish this plan.