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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 daily.

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1
PipelinesStart here. 20 questions · ~160 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
Choose Delta for Lakehouse PipelinesEasy

Design a Databricks lakehouse pipeline and defend choosing Delta Lake over Iceberg and Hudi for mixed batch and streaming workloads.

Berkshire Hathaway Specialty Insurance
Design Enterprise Data Lake ArchitectureMedium

Design an AWS data lake architecture handling 12 TB/day batch data and 80K events/sec with governed bronze, silver, and gold layers.

InfrastructureETLData ModelingBerkshire 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
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2
SQL & Data Manipulation5 questions + 3 drills · ~70 min
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
Simplify Reporting Queries with CTEsEasy

Explain how CTEs make complex PostgreSQL queries easier to read, debug, and maintain in reporting workflows.

SubqueriesJoinsCTEsBerkshire 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
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
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
Cleaning a Messy DatasetMedium
Practice
Practice drill

Filter invalid game events and normalize event names using PostgreSQL string and null handling.

missing valuesdata cleaningnull handlingQuantiumScopelyCarvana
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The finish line: interview-readyComplete all 25 questions plus 3 hands-on drills to finish this plan.