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Prep plan
Updated weekly · Last refresh Oct 17

Ernst & Young Advisory Services Sdn Bhd Data Engineer Interview Questions

The questions to prepare for a Ernst & Young Advisory Services Sdn Bhd Data Engineer interview. Questions from real interview reports rank first. Updated daily.

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1
PipelinesStart here. 10 questions · ~81 min
Diagnose Slow Dashboard PipelinesEasy
Recently asked

Approach for finding and fixing a slow dashboard pipeline, from source ingestion to warehouse queries.

InfrastructureToolsQualityErnst & Young Advisory Services Sdn Bhd
Large Dataset Analysis PipelineEasy
Recently asked

Discuss a large-scale data analysis project with focus on the pipeline, tooling, and data quality approach.

ToolsData ModelingQualityErnst & Young Advisory Services Sdn Bhd
Integrating Multiple Data SourcesEasy
Recently asked

Common pipeline issues when combining multiple data sources, including schema mismatch, data quality, orchestration, and duplicate handling.

ETLData ModelingQualityErnst & Young Advisory Services Sdn Bhd
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2
SQL & Data Manipulation6 questions + 3 drills · ~78 min
Normalization vs Reporting DenormalizationMedium
Recently asked

Explain normalization for data integrity and when denormalization is useful for faster reporting and simpler analytical queries.

performancenormalizationdata integrityErnst & Young Advisory Services Sdn Bhd
Structured vs Unstructured Data BasicsEasy
Recently asked

Explain how structured and unstructured data differ in format, storage, and how easily they can be queried with SQL.

Data WranglingETLErnst & Young Advisory Services Sdn Bhd
Scalable Database DesignHard
Recently asked

Tests database design tradeoffs for scale, performance, and maintainability.

JoinsAggregationsData ModelingErnst & Young Advisory Services Sdn Bhd
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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3
Coding3 questions · ~24 min
Automating Data CleaningMedium
Recently asked

Tests ability to operationalize data cleaning with repeatable, maintainable scripts.

Hash TablesArraysStringsErnst & Young Advisory Services Sdn Bhd
Python Data Transformation FunctionMedium
Recently asked

Tests practical Python skills for transformations and correctness of data processing.

Hash TablesArraysStringsErnst & Young Advisory Services Sdn Bhd
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4
Behavioral & Leadership10 questions · ~81 min
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The finish line: interview-readyComplete all 29 questions plus 3 hands-on drills to finish this plan.