Top 45
Prep plan
Updated weekly · Last refresh Aug 30

Attentive Data Engineer Interview Questions

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

45questions
~6htotal time
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1
SQL & Data ManipulationStart here. 15 questions + 2 drills · ~146 min
Compute Session Durations and GapsMedium
Practice

Use window functions to calculate session length and flag user session gaps over 30 minutes.

sql queriesAttentive
Simplify Reporting Queries with CTEsEasy

Explain how CTEs make complex PostgreSQL queries easier to read, debug, and maintain in reporting workflows.

SubqueriesJoinsCTEsAttentive
Running Totals for Sales ReportingMedium

Explain how to calculate cumulative totals in SQL using window functions, ordering, and optional pre-aggregation.

Window FunctionsDate FunctionsRunning TotalsAttentive
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 MetricsMedium
Practice
Practice drill

Compute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.

ETLAggregationsData ModelingADP
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2
Pipelines23 questions · ~193 min
Design High-Throughput Event PipelineHard

Design a real-time event pipeline that can handle millions of events per second with sub-second latency.

data pipelineevent processinglatencyAttentive
Choose Kafka vs FlinkEasy

Design a streaming pipeline and justify when Kafka, Flink, or both should be used for ingestion, stateful processing, replay, and low-latency delivery.

Stream ProcessingOrchestrationDependenciesAttentive
Batch vs Streaming Data ProcessingEasy

Compare batch and streaming data processing, including when each fits best in a pipeline.

Stream ProcessingETLBatch ProcessingAttentive
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3
Coding5 questions · ~42 min
Expected Coding AlgorithmsEasy

Tests your ability to anticipate common coding patterns used to evaluate data engineering fundamentals.

Hash TablesArraysStringsAttentive
Using Generators for Memory EfficiencyHard

Tests your understanding of Python iterators and generators to handle large datasets without excessive memory use.

RecursionArraysStringsAttentive
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4
More topics2 questions · ~17 min
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The finish line: interview-readyComplete all 45 questions plus 2 hands-on drills to finish this plan.