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Berkshire Hathaway Specialty Insurance Data Engineer Interview Questions

The questions to prepare for a Berkshire Hathaway Specialty Insurance Data Engineer interview. Questions from real interview reports rank first. Updated weekly.

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1
SQL & Data ManipulationStart here. 5 questions + 3 drills · ~70 min
Combine Multi-Source Operational DataEasy

Explain how UNION and UNION ALL combine operational data from multiple sources and when each should be used.

JoinsData WranglingUnionsBerkshire Hathaway Specialty Insurance
Combine Regional Sales with UNIONEasy

Explain how UNION and UNION ALL combine similarly structured datasets, and when to use each for reporting or consolidation.

Data WranglingUnionsBerkshire Hathaway Specialty Insurance
Compare Periods with LAG and LEADMedium

Explain how LAG and LEAD compare current rows to previous or next periods in time-series SQL analysis.

Window FunctionsLag/LeadDate FunctionsBerkshire Hathaway Specialty Insurance
Window Ranking in Ticket QueuesMedium

Explain SQL window functions and when to use ROW_NUMBER() versus DENSE_RANK() for ranked ticket analysis.

Window FunctionsRankingrow_numberBerkshire Hathaway Specialty Insurance
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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2
Pipelines12 questions · ~96 min
Delta Lake vs ParquetMedium

Conceptual pipeline question on Delta Lake and how it differs from plain Parquet files in data engineering workflows.

delta lakeparquetData ModelingBerkshire Hathaway Specialty Insurance
Backfilling Missing Pipeline DataMedium

Approach for safely backfilling missing data while preserving correctness, idempotency, and data quality.

ETLQualityBerkshire Hathaway Specialty Insurance
Handle PySpark Data SkewMedium

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

Data Qualitypysparkdata skewnessBerkshire Hathaway Specialty Insurance
Batch vs Stream Processing Trade-offsMedium

Compare batch and stream processing across latency, complexity, cost, and data quality in a modern analytics pipeline.

InfrastructureStream ProcessingETLBerkshire Hathaway Specialty Insurance
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The finish line: interview-readyComplete all 17 questions plus 3 hands-on drills to finish this plan.