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Prep plan
Updated weekly · Last refresh Aug 30

Verily Data Engineer Interview Questions

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

14questions
~2htotal time
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1
PipelinesStart here. 7 questions · ~56 min
Data Quality in ETL PipelinesEasy
Recently asked

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityVerily
Scalable Clinical Data IngestionMedium
Recently asked

Tests your approach to building reliable, scalable ingestion for high-volume clinical signals.

scalabilitydata ingestionVerily
Data Quality Across Disparate SourcesMedium
Recently asked

Tests your methods for validation, reconciliation, and maintaining consistency across heterogeneous datasets.

Data Qualitydata integrationVerily
Multimodal Clinical Data PipelineMedium
Recently asked

Tests your ability to build ingestion and normalization for multimodal healthcare data.

data pipelinenormalizationVerily
Secure ETL for PrivacyMedium
Recently asked

Tests your security and privacy controls for regulated healthcare data pipelines.

data securitydata privacyVerily
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2
Behavioral & Leadership5 questions · ~40 min
Explaining Technical Trade-offs ClearlyMedium
Recently asked

Tests whether you can translate complex engineering trade-offs into clear business decisions for non-technical stakeholders.

technical communicationTrade-offsStakeholder ManagementVerily
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3
More topics2 questions · ~16 min
FHIR Compliance at ScaleMedium
Recently asked

Tests your understanding of FHIR constraints, evolution, and operational pitfalls in large systems.

scalabilityData StructuresVerily
Data Governance in Regulated HealthcareMedium
Recently asked

Tests your governance design for access control, lineage, auditability, and compliance.

Verily

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
SQL for Consecutive Treatment GapsHard
Practice
Practice drill

Identify patient treatment intervals exceeding 90 days using a self-join, MAX aggregation, and date subtraction.

sqlVerily
Rolling Retention Rates Across SitesHard
Practice
Practice drill

Calculate site-level rolling 30-day patient retention using self-joins, conditional aggregation, and window functions.

Window FunctionssqlVerilySyneos Health
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 14 questions plus 3 hands-on drills to finish this plan.