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Updated weekly · Last refresh Aug 30

Mirakl Data Engineer Interview Questions

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

32questions
~4htotal time
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1
PipelinesStart here. 10 questions · ~80 min
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityMirakl
Data Quality and Schema EvolutionMedium

Approach for handling schema changes and data quality checks in a high-volume data lake pipeline.

schema evolutionData ModelingQualityMirakl
Manage Terraform Infrastructure DriftMedium

Approach for detecting, monitoring, and remediating drift in a Terraform-managed environment.

InfrastructureToolsQualityMirakl
Monitor a Mission Critical PipelineMedium

Design a monitoring and alerting approach for a mission critical pipeline, covering system health, data quality, and operational response.

InfrastructureToolsQualityMirakl
Docker vs Containers and Dockerfile OptimizationMedium

Tests container fundamentals and your ability to optimize build and runtime for data pipelines.

dockercontainerizationoptimizationMirakl
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2
Behavioral & Leadership20 questions · ~160 min
Presenting to Business and ITMedium

Tests communication across mixed audiences, stakeholder management, and the ability to connect business value to technical product detail.

presentation skillsStakeholder ManagementCommunicationMirakl
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3
More topics2 questions · ~16 min
Optimizing Slow SQL and Spark JoinsHard

Tests performance tuning skills for SQL and distributed processing at scale.

Joinsquery optimizationsparkMirakl
SQL Indexing and ACIDHard

Tests fundamentals of database performance and transactional guarantees.

design patternsACIDdatabase conceptsMirakl

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Cohort Conversion ComparisonMedium
Practice
Practice drill

Compare Mirakl buyer cohort conversion rates using aggregation, a LEFT JOIN, and RANK window functions.

Window FunctionsCohort AnalysisAggregationsMirakl
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 32 questions plus 3 hands-on drills to finish this plan.