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Prep plan
Updated weekly · Last refresh Aug 30

ConcertAI Data Engineer Interview Questions

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

28questions
~4htotal time
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1
PipelinesStart here. 20 questions · ~171 min
Batch vs Stream Processing Trade-offsMedium

Compare batch and stream processing across latency, complexity, cost, and data quality in a modern analytics pipeline.

InfrastructureStream ProcessingETLConcertAI
Cloud Platform Experience for PipelinesMedium

Describe practical experience building pipelines on AWS, including orchestration, security, and data quality.

InfrastructureETLData ModelingConcertAI
Handling Missing Data in PipelinesMedium

Approach for handling missing data in an ML data pipeline, including validation, imputation, and safe downstream consumption.

InfrastructureETLBatch ProcessingConcertAI
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2
Coding4 questions · ~34 min
Time Complexity for Data AlgorithmsMedium

Tests understanding of algorithmic efficiency and how it affects large-scale data processing.

Hash TablesMathArraysConcertAI
Deduplicating Records FunctionMedium

Tests algorithmic thinking and practical handling of duplicates for reliable datasets.

Hash TablesArraysSortingConcertAI
API to Database Python ScriptMedium

Tests ability to build reliable data ingestion code from APIs into persistent storage.

Hash TablesArraysSortingConcertAI
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3
More topics4 questions · ~34 min
Top Customers by Sales RevenueEasy
Practice

Use GROUP BY and SUM to rank the top 10 customers by total revenue from a single sales table.

RankingGroup ByAggregationsConcertAI
Optimizing a Slow QueryMedium

Tests skill in diagnosing and improving query performance using practical techniques.

Joinsquery optimizationAggregationsConcertAI
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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 28 questions plus 2 hands-on drills to finish this plan.