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Updated weekly · Last refresh Aug 30

Hilton Grand Vacations Data Engineer Interview Questions

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

16questions
~2htotal time
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1
CodingStart here. 3 questions · ~27 min
Deduplicating Records FunctionEasy
Practice

Remove duplicate Hilton Grand Vacations records by identifier while preserving first-seen order using a hash set.

Hash TablesArraysSortingHilton Grand Vacations
Python Data Transformation BasicsEasy

Tests your practical Python skills for building reliable data transformations.

Hash TablesArraysStringsHilton Grand Vacations
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2
Pipelines9 questions · ~82 min
Data Modeling Tools and ArchitectureEasy

Preferred tools and patterns for data modeling and pipeline architecture in a modern data platform.

InfrastructureToolsData ModelingHilton Grand Vacations
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityHilton Grand Vacations
Real-Time Dashboard Pipeline DesignHard

Approach for building near-real-time dashboard pipelines with streaming, orchestration, and data quality controls.

Stream ProcessingSchedulingDependenciesHilton Grand Vacations
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3
SQL & Data Manipulation4 questions + 3 drills · ~66 min
Optimize SQL Query PerformanceHard

Tests ability to diagnose bottlenecks and apply indexing, query rewriting, and execution-plan driven tuning.

database managementHilton Grand Vacations
SQL With On-Prem DatabasesEasy

Tests your hands-on SQL experience with on-prem relational databases and data extraction.

JoinsData WranglingAggregationsHilton Grand Vacations
Handling Missing ValuesMedium

Tests your approach to data quality and reliable transformations for downstream analytics.

SubqueriesData WranglingCase WhenHilton Grand Vacations
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
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The finish line: interview-readyComplete all 16 questions plus 3 hands-on drills to finish this plan.