Top 49
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Updated weekly · Last refresh Aug 30

Meta Platforms Data Engineer Interview Questions

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

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1
SQL & Data ManipulationStart here. 13 questions + 2 drills · ~146 min
Top 10 Customers SQLEasy
Practice
Recently asked

Use SUM, GROUP BY, ORDER BY, and LIMIT to find the top 10 Healthfirst Marketplace customers by purchase total.

RankingGroup ByAggregationsMeta Platforms
OLTP vs OLAP Database DesignMedium
Recently asked

Explain OLTP vs OLAP designs, including schema shape, workload patterns, and when each is appropriate in a data platform.

financial dataperformanceData ModelingMeta Platforms
Window Ranking in Ticket QueuesMedium
Recently asked

Explain SQL window functions and when to use ROW_NUMBER() versus DENSE_RANK() for ranked ticket analysis.

Window FunctionsRankingrow_numberMeta Platforms
30-Day Campaign User RetentionHard
Practice
Practice drill

Calculate 30-day retention for users exposed to a Google Ads campaign using CTEs, joins, aggregations, and date filtering.

Window FunctionsDate FunctionsAggregationsGoogleMeta Platforms
Weekly Service KPI by TeamMedium
Practice
Practice drill

Analyze weekly service delivery performance by team using joins, a CTE, date aggregation, and KPI calculations.

KPIJoinssqlDeloitteReputation
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2
Coding12 questions · ~117 min
Two Sum with TargetEasy
Practice
Recently asked

Use a hash map to find two array elements that sum to a target in O(n) time.

Hash TablesArraysStringsMeta Platforms
Max Points With Category ConstraintsEasy
Practice

Use a hash map and top-three greedy selection to maximize points from books in distinct categories.

pythonMeta Platforms
Maximum Average SubarrayMedium
Practice

Find the maximum average of any subarray of length at least k using binary search and transformed prefix sums.

Dynamic ProgrammingMeta Platforms
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3
Pipelines7 questions · ~68 min
Optimize Multi-Terabyte ETL PipelineMedium
Recently asked

Explain how you improved a slow ETL pipeline on multi-terabyte data, including bottleneck analysis, tuning choices, and validation.

ETL optimizationdata processingperformanceMeta Platforms
Data Quality vs SpeedHard
Recently asked

Tests your judgment in designing reliable pipelines under latency and throughput constraints.

IdempotencyBackfillingQualityMeta Platforms
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4
Behavioral & Leadership17 questions · ~165 min
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The finish line: interview-readyComplete all 49 questions plus 2 hands-on drills to finish this plan.