Top 21
Prep plan
Updated weekly · Last refresh Aug 30

Headspace Data Engineer Interview Questions

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

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1
SQL & Data ManipulationStart here. 5 questions + 2 drills · ~67 min
7-Day Rolling DAU on FacebookMedium
Practice

Compute daily distinct active users and a 7-day rolling average using a CTE and window function.

Headspace
Star vs Snowflake for Sales AnalyticsMedium

Compare star and snowflake schemas for warehouse design, including trade-offs in normalization, query simplicity, and analytics performance.

JoinsData WranglingGroup ByHeadspace
Model Journey Data for FunnelsMedium

Tests your ability to design analytics-friendly schemas for funnel and journey analysis.

AggregationsData ModelingHeadspace
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
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2
Pipelines9 questions · ~84 min
Star vs Snowflake SchemaEasy

Compare star and snowflake schemas in a warehouse pipeline, including structure and transformation trade-offs.

snowflake schemastar schemaData ModelingHeadspace
Backfill While Preserving Real TimeHard

Approach for running large historical backfills without breaking real-time pipeline freshness or correctness.

Stream ProcessingDependenciesBackfillingHeadspace
Handle PySpark Data SkewMedium

Approach for detecting and mitigating skew in PySpark pipelines using partitioning, join strategies, and runtime monitoring.

Data Qualitypysparkdata skewnessHeadspace
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3
Behavioral & Leadership5 questions · ~47 min
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4
More topics2 questions · ~19 min
Merge Overlapping Time IntervalsMedium
Practice

Merge overlapping intervals by sorting on start time, then scanning once to combine intersecting ranges.

time complexityAlgorithmsperformance analysisHeadspace
Flatten Nested JSON in PythonMedium

Tests your ability to write correct Python for transforming semi-structured event data.

json parsingData WranglingpythonHeadspace

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The finish line: interview-readyComplete all 21 questions plus 2 hands-on drills to finish this plan.