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The Federal National Mortgage Association - Fannie Mae Data Engineer Interview Questions

The questions to prepare for a The Federal National Mortgage Association - Fannie Mae Data Engineer interview. Questions from real interview reports rank first. Updated daily.

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1
SQL & Data ManipulationStart here. 8 questions + 3 drills · ~94 min
Customer Orders: LEFT vs INNER JOINEasy

Explain how INNER JOIN and LEFT JOIN differ, and when to use each for matched-only versus all-left-row analysis.

JoinsData WranglingGroup ByThe Federal National Mortgage Association - Fannie Mae
Validating DataFrame MismatchesMedium

Tests your ability to detect and investigate discrepancies between datasets using programmatic checks.

data validationThe Federal National Mortgage Association - Fannie Mae
Join Types in Data PipelinesMedium

Evaluates your understanding of join semantics and their impact on pipeline correctness.

data pipelinesqljoin typesThe Federal National Mortgage Association - Fannie Mae
Production SQL Performance TuningHard

Evaluates advanced performance tuning skills for large-scale production SQL workloads.

performancequery optimizationsqlThe Federal National Mortgage Association - Fannie Mae
SQL Moving Average With WindowsMedium
Practice
Practice drill

Calculate each customer’s 30-day moving average of daily transaction totals using aggregation and a PostgreSQL window frame.

Data AnalysisJJP Morgan ChaseFinacleThe Federal National Mortgage Association - Fannie Mae
Using SQL and PythonMedium
Practice
Practice drill

Use SQL aggregation and Python validation to explain how a workplace data problem was solved and measured.

JoinsProblem SolvingsqlLalamove
SQL Duplicate Consumer ProfilesMedium
Practice
Practice drill

Identify likely duplicate consumer profiles using normalized partial names and matching locations.

data cleaningnull handlingJoinsWindfall Data
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2
Behavioral & Leadership9 questions · ~72 min
Explaining a Technical Concept ClearlyEasy

Tests communication, ownership, and stakeholder management when translating technical complexity into actionable business understanding.

Problem SolvingData Structurestechnical fundamentalsThe Federal National Mortgage Association - Fannie Mae
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3
More topics3 questions · ~24 min
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityThe Federal National Mortgage Association - Fannie Mae
Python Classes BasicsEasy

Assesses foundational understanding of Python object-oriented concepts.

pythonoopThe Federal National Mortgage Association - Fannie Mae
Fixing Data Pipeline FlawsMedium

Tests your ability to debug pipeline issues and drive reliable fixes.

Data Qualitydata pipelineProblem SolvingThe Federal National Mortgage Association - Fannie Mae

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