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Updated weekly · Last refresh Aug 30

Huntington Bancshares Data Engineer Interview Questions

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

13questions
~2htotal time
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1
PipelinesStart here. 6 questions · ~48 min
Data Quality and Schema EvolutionMedium

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

schema evolutionData ModelingQualityHuntington Bancshares
Design Scalable Pipeline InfrastructureHard

Design the core pipeline infrastructure for a new project, with attention to orchestration, data quality, idempotency, and future scale.

InfrastructureToolsQualityHuntington Bancshares
Optimize a Large Data WorkflowMedium

Approach for improving pipeline efficiency while keeping the same business logic and outputs.

InfrastructureETLQualityHuntington Bancshares
Troubleshooting Failed ETLMedium

Tests incident diagnosis skills across pipelines, dependencies, and data quality signals.

ETLTroubleshootingHuntington Bancshares
Handling Large-Scale Production DataMedium

Tests your experience with scale, reliability, and operational practices for production data workloads.

production environmentdata handlingHuntington Bancshares
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2
Behavioral & Leadership5 questions · ~40 min
Clarifying Vague Stakeholder RequirementsMedium

Tests how you gather requirements under ambiguity by using stakeholder management, structured communication, and problem clarification.

User NeedsDealing With AmbiguityrequirementsHuntington Bancshares
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3
More topics2 questions · ~16 min
Optimizing Cloud Data PlatformsMedium

Tests performance tuning, platform selection tradeoffs, and operational understanding of cloud data systems.

Performance Tuningcloud platformsHuntington Bancshares
Ensuring Data Quality in MigrationMedium

Tests your approach to validating, reconciling, and maintaining data correctness during migrations.

Data Qualityconsistencydata migrationHuntington Bancshares

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
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
Handle Missing Financial Input ValuesMedium
Practice
Practice drill

Use joins, CTEs, and CASE logic to flag and fill missing financial fields for Qlik planning records.

Data WranglingETLQualityQlik
The finish line: interview-readyComplete all 13 questions plus 3 hands-on drills to finish this plan.