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Roche Data Engineer Interview Questions

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

20questions
~3htotal time
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1
PipelinesStart here. 5 questions · ~41 min
Data Quality and Schema EvolutionMedium

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

schema evolutionData ModelingQualityRoche
Handle Late Data in BatchMedium

Approach for handling late-arriving records in a batch ETL pipeline without breaking correctness or forcing full reloads.

Batch ProcessingIdempotencyDependenciesRoche
Batch and Streaming Data Lake PipelineHard

Tests your ability to design robust pipelines for clinical trial data with both batch and streaming ingestion.

data integrationStream ProcessingBatch ProcessingRoche
Privacy-Preserving GenAI for PatientsHard

Evaluates privacy-preserving design choices for using genAI on sensitive healthcare data.

GenAIdata privacyRoche
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2
Behavioral & Leadership12 questions · ~97 min
Explaining Technical Complexity to Business PartnersEasy

Tests communication of complex technical ideas to non-technical partners, including clarity, stakeholder alignment, and influence on decisions.

Stakeholder ManagementCommunicationexplanationRoche
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3
More topics3 questions · ~24 min
Flatten Nested JSON in PythonMedium

Tests your Python skills for transforming semi-structured data into database-ready structures.

json parsingData WranglingpythonRoche
Purpose of Validation DatasetsMedium

Assesses your understanding of model evaluation and preventing overfitting in data workflows.

validationRoche
Live Coding: String and FilteringEasy

Tests your ability to write correct, efficient code under live interview conditions.

ArraysStringspythonRoche

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
SQL Top Products by RegionMedium
Practice
Recently asked
Practice drill

Rank Roche products by revenue within each region for the last completed quarter using CTEs, joins, aggregation, and RANK().

JoinsRankingAggregationsAubay SpainRocheAyes - Management & Technology Consulting
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
SQL Bookstore Schema PracticeEasy
Practice
Practice drill

Use a CTE, joins, and distinct aggregates to calculate Meta Logistics bookstore payment metrics.

sql queriessqlpythonMeta Logistics
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