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Prep plan
Updated weekly · Last refresh Aug 30

Exl Data Engineer Interview Questions

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

50questions
~7htotal time
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1
PipelinesStart here. 27 questions · ~218 min
Data Quality in ETL PipelinesEasy
Recently asked

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityExl
Diagnose an Integration Pipeline IssueMedium
Recently asked

Structured approach to diagnose failures in an ETL integration, from source extraction through orchestration, data quality, and idempotent recovery.

ToolsDependenciesQualityExl
Cloud Storage in Data PipelinesEasy
Recently asked

Discuss how cloud storage fits into ETL pipelines, including staging, data quality, and operational monitoring.

InfrastructureETLExl
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2
Coding3 questions · ~24 min
Explain Time ComplexityEasy
Recently asked

Tests ability to analyze algorithm efficiency and communicate tradeoffs.

MathArraysExl
Parse Complex JSON in PythonHard
Recently asked

Tests coding ability to correctly parse and transform nested JSON into structured outputs.

RecursionArraysStringsExl
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3
SQL & Data Manipulation13 questions + 3 drills · ~135 min
Handling Duplicates and Nulls in SQLEasy

Explain practical SQL approaches for identifying, removing, and preventing duplicates and NULL-related data quality issues.

Data WranglingGroup ByCase WhenExl
SQL and ADF and Spark QuestionsMedium

Evaluates experience integrating SQL with ADF and Spark for pipelines.

sqlsparkExl
SQL Normalization MethodsMedium

Tests understanding of SQL normalization and its impact on data design and query behavior.

normalizationsqlExl
SQL for Running AverageMedium
Practice
Practice drill

Calculate five-day rolling service averages using daily aggregation, a calendar join, and PostgreSQL window functions.

queriessqlExlEXL ServiceSystem One
Top Customers by Region VolumeMedium
Practice
Practice drill

Find the top 3 customers in each region by transaction volume using joins, aggregation, and window ranking.

Window FunctionsJoinsRankingJPMorganChaseSilicon Valley BankNavi
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
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4
Behavioral & Leadership7 questions · ~57 min
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The finish line: interview-readyComplete all 50 questions plus 3 hands-on drills to finish this plan.