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Peterson Institute for International Economics Data Engineer Interview Questions

The questions to prepare for a Peterson Institute for International Economics Data Engineer interview. Questions from real interview reports rank first. Updated daily.

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1
Behavioral & LeadershipStart here. 4 questions · ~32 min
Handling Tough Code Review FeedbackMedium

Tests how you receive peer feedback in code reviews, respond constructively, and turn critique into better code and stronger team habits.

code reviewsCommunicationfeedbackPeterson Institute for International Economics
Coaching a Junior Team MemberEasy

Tests mentorship through specific feedback, communication style, and ownership of another person’s development and outcomes.

MentorshipfeedbackLeadershipPeterson Institute for International Economics
Prioritizing Across Competing ProjectsMedium

Tests prioritization under pressure across multiple projects, including time management, stakeholder communication, and ownership of trade-offs.

time managementmultitaskingPrioritizationPeterson Institute for International Economics
Defining Success with StakeholdersMedium

Assesses requirement gathering and translating stakeholder goals into measurable outcomes.

Stakeholder ManagementCommunicationPeterson Institute for International Economics
2
More topics4 questions · ~32 min
Cleaning Messy Campaign DataMedium

Explain how to clean messy campaign data using SQL with validation, NULL handling, and structured transformation steps.

null handlingData Wranglingdata integrityPeterson Institute for International Economics
Cloud Scaling for Data InfrastructureMedium

Assesses your ability to scale data systems using cloud services and best practices.

cloud infrastructurescalabilityPeterson Institute for International Economics
Automating Manual WorkflowsMedium

Evaluates your automation mindset and impact on operational efficiency.

process improvementefficiencyAutomationPeterson Institute for International Economics
Debugging a Pipeline IssueHard

Tests your troubleshooting skills and ability to restore reliable pipeline behavior.

data pipelinesPeterson Institute for International Economics

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Classify Clinical Measurements by Data QualityMedium
Practice
Practice drill

Classify missing and corrupt clinical measurements and retain only valid values for analysis.

missing valuesdata cleaningnull handlingZZifo RnD SolutionsBristol Myers Squibb
Detect Duplicate RegistrationsHard
Practice
Practice drill

Identify near-duplicate Credit Karma registrations by normalizing email variations and comparing registration timestamps.

data cleaningDate Functionsnull handlingCredit Karma
Impute Sparse Assessment ScoresHard
Practice
Practice drill

Use CTEs, joins, CASE, and null handling to clean sparse assessment scores and impute missing values per question.

null handlingData Wranglingdata integrityMercor
The finish line: interview-readyComplete all 8 questions plus 3 hands-on drills to finish this plan.