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Top 19
Prep plan
Updated weekly · Last refresh Aug 30

Cegeka Data Engineer Interview Questions

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

19questions
~3htotal time
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1
PipelinesStart here. 10 questions · ~87 min
Real-Time Dashboard Data PipelineMedium

Design a streaming pipeline that keeps dashboard data fresh and accurate for operational reporting.

InfrastructureStream ProcessingOrchestrationCegeka
Cleaning Missing Values in PipelinesEasy

Approach for handling missing values in a pipeline with data quality checks and repeatable transformations.

Data WranglingETLQualityCegeka
Data Integration Tools ExperienceEasy

Discuss the data integration tools you have used and how they fit into ETL, orchestration, and data quality workflows.

InfrastructureToolsETLCegeka
Cloud AI Deployment Pipeline ExperienceMedium

Discuss experience building cloud-based AI pipelines, including orchestration, processing patterns, infrastructure choices, and data quality controls.

InfrastructureToolsQualityCegeka
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2
Behavioral & Leadership6 questions · ~52 min
Balancing Debt Against Feature DeliveryMedium

Tests prioritization and ownership when balancing technical debt with feature delivery under stakeholder pressure.

technical debtfeature deliveryProject ManagementCegeka
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3
More topics3 questions · ~26 min
Top Customers SQL QueryEasy
Practice

Aggregate customer sales volume and return Pyramid Consulting's top 10 customers in descending order.

RankingGroup ByAggregationsCegeka
Python Data TransformationMedium

Tests your ability to design robust Python transformations for data engineering workflows.

Hash TablesArraysStringsCegeka
Optimizing a Slow QueryMedium

Tests your approach to diagnosing query bottlenecks and improving performance safely.

Joinsquery optimizationAggregationsCegeka

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Hands-on SQL practiceWrite and run real queries in the editor. 2 drills · ~20 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
The finish line: interview-readyComplete all 19 questions plus 2 hands-on drills to finish this plan.