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Updated weekly · Last refresh Aug 30

Opendoor Data Engineer Interview Questions

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

15questions
~2htotal time
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1
CodingStart here. 4 questions · ~37 min
Longest Substring Without RepeatsMedium
Practice

Find the longest substring with all unique characters using a sliding window.

Hash TablesStringsTwo PointersOpendoor
Most Efficient Sorting AlgorithmEasy

Tests your knowledge of algorithmic efficiency and time complexity for comparison-based sorting.

MathArraysSortingOpendoor
Explaining Your Coding ProcessEasy

Tests your clarity of reasoning, debugging habits, and communication during implementation.

ArraysStringsGreedyOpendoor
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2
Pipelines9 questions · ~83 min
Describe a Complex Transformation PipelineMedium

Explain a complex ETL transformation you built, including the main challenges and how you handled them.

ETLData ModelingQualityOpendoor
Design Scalable Pipeline InfrastructureHard

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

InfrastructureToolsQualityOpendoor
Diagnose an Integration Pipeline IssueMedium

Structured approach to diagnose failures in an ETL integration, from source extraction through orchestration, data quality, and idempotent recovery.

ToolsDependenciesQualityOpendoor
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3
More topics2 questions · ~19 min
SQL vs NoSQL for Go-to-Market DataEasy

Explain how SQL and NoSQL differ in schema, consistency, scaling, and Demandbase-style analytics use cases.

JoinsData WranglingOpendoor
Handle Missing ValuesEasy

Tests data quality judgment and appropriate imputation or exclusion strategies for analytics.

Data WranglingCase WhenAggregationsOpendoor
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 15 questions plus 3 hands-on drills to finish this plan.