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How do you handle disagreement with a co-worker?

Behavioraleasy0.7 min readPremium

Situation: A senior colleague advocated for a single monolithic dbt project; I favored domain-based multi-repos. We were at an impasse before a major migration. Task: Reach a decision that served the team without creating resentment. Action: I proposed a timeboxed spike:...

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Frequency
Low
Asked at 1 company
Category
144
questions in Behavioral
Difficulty Split
100E|18M|26H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Gartner

Why This Question Matters

This easy-level Behavioral question appears frequently in data engineering interviews at companies like Gartner. While less common, it tests deeper understanding that distinguishes strong candidates.

How to Approach This

Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.

Expert Answer
132 words

Situation: A senior colleague advocated for a single monolithic dbt project; I favored domain-based multi-repos. We were at an impasse before a major migration. Task: Reach a decision that served the team without creating resentment. Action: I proposed a timeboxed spike: prototype both approaches for one domain and measure—build time, test latency, merge conflict frequency. I documented both options in a shared doc with pros/cons and assumptions. We ran the spike over 3 days. Results favored multi-repo for our scale (12 engineers, 50+ models). I shared findings in a team review; we adopted multi-repo. I made sure my colleague's concerns (discovery, consistency) were addressed in the design. Result: We shipped the migration on time; the colleague later became an advocate for the approach. Pro tip: Data beats opinion—prototype when stakes are high.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According to DataEngPrep.tech, this is one of the most frequently asked Behavioral interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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