Meta Data Manipulation (SQL/Python) Interview Questions
Practice 1,159 real Meta interview questions for 2026. Covers top categories — Coding & Algorithms, Analytics & Experimentation, Data Manipulation (SQL/Python), Behavioral & Leadership, and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Data Engineer, and Product Manager roles. Real questions from actual interviews with detailed solutions. Expect a software-engineering-heavy loop: timed algorithmic coding (trees, arrays, graph/maze problems, delimiter/CSV parsing), system-design prompts like leaderboards, flight search and online-judge architectures, and an increasingly common AI-assisted coding round that mirrors real workflows. Data Scientist rounds emphasize product analytics and experimentation—designing tests, diagnosing spend drops and bots, evaluating unconnected content, and writing SQL for multi-account, seller, and vehicle metrics. Machine Learning Engineer questions skew toward recommender and ranking work (place and friend recommendation, sparse-matrix ops, linear-regression derivations, newsfeed dislike models). Data Engineers focus on data modeling, ETL, capacity calculations, reservations/utilization queries, and production SQL/Python tasks. For interview preparation, prioritize timed coding practice, system-design templates, rigorous SQL drills (joins/CTEs/aggregation), clear A/B-testing frameworks, and concise STAR behavioral stories tied to measurable impact.
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Convert multi-currency revenue to USD totals
This question evaluates a candidate's competency in converting multi-currency revenue into USD totals by aligning event dates with FX rates, handling ...
Compare performance of FB vs IG Stories
This question evaluates a data scientist's competency in experimental design, causal inference, attribution modeling, metric selection, and decision-o...
Compute daily active ads
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Evaluate AI-assisted ads creation feature
This question evaluates a data scientist's competence in experimental design, metric selection, causal inference, and balancing business metrics with ...
Analyze and mitigate fake advertiser accounts
This question evaluates competency in fraud detection analytics, including operationally defining fake advertiser accounts, designing longitudinal met...
Write SQL for seller and category metrics
This question evaluates proficiency in SQL data manipulation—principally joins, aggregations, grouping, filtering, date arithmetic, and safe handling ...
How to evaluate Shop ad upranking
This question evaluates a data scientist's competency in causal experimentation, metric design, uplift and channel-substitution analysis, heterogeneou...
How would you evaluate upranking shop ads?
This question evaluates a candidate's competency in ad-ranking intervention evaluation, causal inference and experimentation design, metric definition...
Implement weighted random sampling with preprocessing
This question evaluates algorithm design and probabilistic reasoning for weighted random sampling, including data-structure preprocessing, time-space ...
Solve four OA string/array/matrix/graph tasks
This multi-part prompt evaluates proficiency in core programming competencies: string parsing and character classification, simulation/greedy processi...
Solve frequency and tree-completeness problems
These two problems evaluate competency in frequency counting and selection algorithms for identifying top-k elements and in binary tree structure anal...
Design content moderation for a posting app
This question evaluates a candidate's ability to design content-moderation features, covering competencies in scalable system design, API and data mod...
Determine feasibility and clean parentheses string
This pair of problems evaluates proficiency with graph algorithms (dependency modeling and cycle detection/topological ordering) and string processing...
Compute the next lexicographic permutation
This question evaluates understanding of permutations and lexicographic ordering, in-place array manipulation, and algorithmic reasoning about time an...
Design a Top-K trending items service
This question evaluates competency in large-scale system design, real-time streaming ingestion, distributed aggregation, and trade-offs between exact ...
Compute sparse dot product and count islands
You are asked to solve two coding problems. Problem 1: Sparse vector dot product Given two vectors A and B of the same length n (potentially large, e....
Maximize concatenation length with unique chars
This question evaluates understanding of string manipulation, set-based uniqueness constraints, and combinatorial subset selection for maximizing conc...
Discuss achievements, ambiguity handling, growth, and conflict management
Discuss achievements, ambiguity handling, growth, and conflict management Behavioral & Leadership Interview Prompts (Software Engineer — Onsite) Conte...
Demonstrate ownership and conflict resolution
Demonstrate ownership and conflict resolution Behavioral: 0→1 Data Initiative, Prioritization, and Cross-Functional Leadership Context: Onsite intervi...
Define and validate product metrics
Define and validate product metrics End-to-End Analytics Design for a New Product Feature Context: You are the data engineer partnering with product, ...