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Updated weekly · Last refresh Oct 17

University of Rochester Medical Center Data Engineer Interview Questions

The questions to prepare for a University of Rochester Medical Center Data Engineer interview. Questions from real interview reports rank first. Updated daily.

17questions
~3htotal time
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1
PipelinesStart here. 13 questions · ~117 min
Data Warehousing in PipelinesEasy

Explain what a data warehouse is and why it matters in analytics pipelines.

InfrastructureETLData ModelingUniversity of Rochester Medical Center
Structured vs Unstructured DataEasy

Explain how structured and unstructured data differ, and why that matters for pipeline design and downstream processing.

ETLData ModelingQualityUniversity of Rochester Medical Center
Design an End-to-End Data PipelineMedium

Approach for designing an end-to-end data pipeline from ingestion through transformation, storage, and downstream consumption.

data pipelinedesigningestionUniversity of Rochester Medical Center
Diagnose an Integration Pipeline IssueMedium

Structured approach to diagnose failures in an ETL integration, from source extraction through orchestration, data quality, and idempotent recovery.

ToolsDependenciesQualityUniversity of Rochester Medical Center
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2
SQL & Data Manipulation3 questions + 3 drills · ~57 min
Optimizing Data Retrieval ProcessesHard

Tests your ability to improve retrieval performance through indexing, query design, and system tuning.

SubqueriesJoinsData WranglingUniversity of Rochester Medical Center
Optimizing a Slow Database QueryHard

Tests your ability to diagnose query performance issues and apply indexing and query plan improvements.

Joinsquery optimizationAggregationsUniversity of Rochester Medical Center
Writing SQL QueriesEasy

Tests ability to write correct SQL for extracting data needed for AAK USA reporting.

SubqueriesJoinsGroup ByUniversity of Rochester Medical Center
Handling Missing DataEasy
Practice
Practice drill

Replace missing sales fields with defined defaults and return a consistently ordered dataset.

missing valuesdata cleaningnull handlingUniversity of MinnesotaThe Home DepotNationwide
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
3
More topics1 question · ~9 min
The finish line: interview-readyComplete all 17 questions plus 3 hands-on drills to finish this plan.