Top 23
Prep plan
Updated weekly · Last refresh Oct 17

StockX Data Engineer Interview Questions

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

23questions
~3htotal time
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1
PipelinesStart here. 14 questions · ~114 min
Diagnose Pipeline Performance DropMedium

Diagnose a sudden pipeline slowdown by tracing latency, throughput, data quality, and orchestration signals across the stack.

InfrastructureDependenciesQualityStockX
Design Real-Time Operations Dashboard PipelineHard

Design a pipeline for a real-time operational dashboard, covering streaming ingestion, modeling, data quality, and dashboard serving.

InfrastructureStream ProcessingQualityStockX
Data Modeling Tools and ArchitectureEasy

Preferred tools and patterns for data modeling and pipeline architecture in a modern data platform.

InfrastructureToolsData ModelingStockX
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2
Coding3 questions · ~25 min
Analyzing Time ComplexityEasy

Tests your ability to reason about algorithmic efficiency and performance implications.

Hash TablesArraysSortingStockX
Deduplicating Records in SQLMedium

Tests your ability to design deduplication logic and handle edge cases in data processing.

Hash TablesArraysSortingStockX
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3
SQL & Data Manipulation5 questions + 3 drills · ~71 min
Schema for Large E-CommerceMedium

Tests your data modeling and schema design for high-volume, multi-entity e-commerce data.

JoinsData WranglingGroup ByStockX
SQL Top 10 Products QueryMedium

Tests your SQL skills for aggregation, filtering by time window, and ranking results.

Date FunctionsRankingAggregationsStockX
Handling Missing ValuesMedium

Tests your practical choices for imputation, filtering, and preserving data quality.

SubqueriesData WranglingCase WhenStockX
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
Python or R Analysis LibrariesMedium
Practice
Practice drill

Count unique respondents by Python or R library and return the most commonly used libraries first.

analytics toolsData ManipulationData WranglingOklahoma City Thunder
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4
More topics1 question · ~8 min
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The finish line: interview-readyComplete all 23 questions plus 3 hands-on drills to finish this plan.