Data Manipulation (SQL/Python) Interview Questions

Showing 241–270 of 446 results

• MetaMedium·Data Scientist
  Resolve Ties for Top-10 Users in SQL Query

  This question evaluates proficiency in SQL ranking and tie-resolution techniques for generating deterministic top-N leaderboards, focusing on handling identical scores while producing an exact set of rows.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Retrieve Ad Metrics and Rates for Last 7 Days

  This question evaluates proficiency in SQL-based data manipulation including joins, conditional aggregation, time-based filtering, and computation of advertising metrics such as impressions, clicks, CTR, and conversion rate.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Retrieve Top Five Ads by Conversions in 30 Days

  This question evaluates a candidate's competency in SQL data manipulation, specifically aggregating event data and applying time-window filters to produce ranked metrics.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Engineer
  Return count and renewal percentage of unreturned good copies

  This question evaluates proficiency in SQL data manipulation, including conditional filtering, NULL handling, aggregation, and computing conditional percentages across related tables.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Engineer
  Return top-3 content per category

  This question evaluates the ability to perform grouped top-k selection, deterministic tie-breaking and ordering, and to reason about algorithmic efficiency when manipulating structured datasets in the Data Manipulation (SQL/Python) domain for a Data Engineer role.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Software Engineer
  Set up a Python interview environment

  This question evaluates proficiency in Python development environment setup, including dependency and virtual environment management, secure handling of environment variables for secrets, tooling for rapid feedback, reproducibility practices, and basic service scaffolding.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Engineer
  Solve Python and SQL data tasks

  This question evaluates data manipulation and engineering competencies by testing Python proficiency with nested data structure handling, complexity analysis and test-case design, alongside SQL proficiency in UTC-aware aggregation and per-user deduplication to compute daily active users; it is categorized as Data Manipulation (SQL/Python) within the data engineering domain. Such problems are commonly asked to assess practical implementation ability and robustness under edge cases, as well as conceptual understanding of time/space complexity and correct date-time handling, reflecting a primarily practical application with elements of conceptual analysis.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write SQL filtering, grouping, CASE, UNION tasks

  This question evaluates proficiency with SQL filtering, aggregation, conditional logic, and set operations—specifically skills around WHERE filtering, GROUP BY/HAVING, CASE bucketing, FLOOR on aggregates, and UNION versus UNION ALL—within the Data Manipulation (SQL/Python) domain and emphasizes practical application of ANSI SQL.

  Data Manipulation (SQL/Python)HR Screen
• MetaMedium·Data Scientist
  Write SQL for CTR and Revenue

  This question tests the ability to join event logs with reference data, perform conditional aggregation to calculate click-through rates (CTR), and apply date-sensitive currency conversions.

  Data Manipulation (SQL/Python)Technical ScreenSQLData AggregationJoin
• MetaMedium·Data Scientist
  Write SQL for Pixel Signal Metrics

  This question evaluates SQL-based data manipulation and analytical competencies, specifically joining and aggregating event and ad performance tables, computing event-weighted metrics and composite data-quality scores (such as validity and match-rate based measures) across a 30-day window.

  Data Manipulation (SQL/Python)Technical Screen
• MetaEasy·Product Analyst
  Write SQL for call pickup and usage metrics

  This question tests the ability to join event logs, filter by session timing, and calculate per-user metrics using window functions or group-by operations.

  Data Manipulation (SQL/Python)OnsiteSQLAggregationJoins
• MetaMedium·Data Scientist
  Write SQL for comment analytics

  This question evaluates proficiency in SQL analytics, specifically joins, filtering, aggregation (distinct counts), percentile functions, time-windowed grouping, handling soft-deleted records, and writing efficient queries via CTEs.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL for daily chats and fast replies

  This question evaluates a candidate's ability to manipulate relational data and reason about temporal event sequences, specifically testing skills in SQL aggregation, distinct counting, deduplication, bidirectional relationship handling, and time-windowed event matching.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Engineer
  Write SQL for library analytics

  This question evaluates proficiency in SQL-based data manipulation and analytical querying, focusing on relational schema navigation, joins, aggregation, filtering, and handling temporal and conditional metrics within a library dataset.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write SQL for multi-account metrics

  This question tests your ability to perform complex aggregations across multiple tables, specifically using conditional logic and joins to compute user engagement metrics.

  Data Manipulation (SQL/Python)Technical ScreenSQLAggregationJoins
• MetaMedium·Data Scientist
  Write SQL for retention, conversion, and churn

  This question evaluates proficiency in SQL-based analytics and time-aware data manipulation, covering cohort and retention computation, conversion and churn metrics, user-level deduplication across platforms, timezone-local day handling, rolling-window comparisons, and calculation of statistical confidence intervals.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL for seller and category metrics

  This question tests the ability to perform complex aggregations, handle date filtering, and calculate performance ratios while managing potential division-by-zero errors in a multi-table SQL environment.

  Data Manipulation (SQL/Python)Technical ScreenSQLAggregationJoins
• MetaMedium·Data Scientist
  Write SQL for social feed metrics and ties

  This question evaluates advanced SQL analytics skills and competency in data modeling for social feed metrics, including relationship joins, viewer-day temporal aggregation, weighted interaction scoring, and per-user top-N ranking.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write SQL to analyze shop visibility

  This question evaluates proficiency in SQL-based time-series and event-data manipulation, including deduplication of consecutive states, window functions, aggregation, cohort analysis, and percentile/summary statistics.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL to compare exclusive category engagement

  This question evaluates SQL-based data manipulation and cohort analysis competencies, including cohort definition, session-level filtering and aggregation for metrics such as user counts, median active days, proportions, and per-user average minutes while applying data-quality constraints over a fixed date window.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL to flag coordinated fake accounts

  This question evaluates proficiency in SQL-based data manipulation, temporal windowing, event-table joins, aggregation and feature engineering for fraud detection, including computing weighted risk_score flags across user activity.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL to infer group-call demand

  This question evaluates SQL-based data manipulation and product-analytics competencies, including temporal sessionization, graph connectivity inference for detecting overlapping 1:1 call loops, deduplication trade-offs (UNION vs UNION ALL), and computation of derived metrics to estimate latent feature demand within the Data Manipulation (SQL/Python) domain. It is commonly asked because it measures practical application of event-time windowing, connected-component reasoning and edge-case handling (e.g., excluding failed connections) for producing daily summary metrics, emphasizing hands-on SQL proficiency over purely conceptual understanding.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write SQL/pandas for KPI anomaly

  This question evaluates proficiency with SQL window functions and equivalent pandas operations for KPI anomaly detection, covering baseline computation using same-weekday medians over eight weeks, per-country and per-post_type Likes-per-DAU metrics with deduplication of users for DAU, outage filtering, attribution of declines between new and existing users, and time-series comparisons like friend-request acceptance rates while explicitly handling duplicates, sparse or missing DAU rows, and timezone issues. It is commonly asked in Data Manipulation (SQL/Python) interviews to assess practical data engineering and analytical skills, primarily testing practical application with an underlying need for conceptual understanding of baselining, attribution, and data-quality edge cases.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write advanced SQL for sales support analytics

  This question evaluates practical SQL data-manipulation skills such as joins, aggregation, window functions, time-based filtering, deduplication, and computation of sales KPIs for rep-level analytics.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write dating profile report with final reviews

  This question evaluates SQL and data-manipulation proficiency, including temporal joins, versioning, time-bounded snapshotting, windowed aggregations, and validation checks for data quality and idempotency.

  Data Manipulation (SQL/Python)Onsite
• MicrosoftMedium·Software Engineer
  Compute most popular location with weights

  This question evaluates a candidate's ability to perform weighted aggregation, data cleaning, tie-breaking logic, and handling of malformed or missing text fields using SQL and/or Python.

  Data Manipulation (SQL/Python)Technical Screen
• MicrosoftMedium·Software Engineer
  Count words in a document robustly

  This question evaluates text-processing and algorithmic engineering skills, specifically precise tokenization rule definition, robust handling of Unicode and punctuation, streaming/large-file processing, unit testing for corner cases, and analysis of time and space complexity.

  Data Manipulation (SQL/Python)Onsite
• MicrosoftMedium·Data Scientist
  Find common friends from directed edges

  This question evaluates a candidate's ability to manipulate relational data and reason about graph reciprocity, specifically testing SQL query formulation, aggregation, deduplication, and indexing for performance in the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Technical Screen
• MicrosoftEasy·Data Scientist
  Query departments and top earners

  This problem tests your ability to aggregate data using window functions to identify top-performing rows within specific groups and perform conditional filtering across joined tables.

  Data Manipulation (SQL/Python)Technical ScreenSQLWindow FunctionsJoins
• MicrosoftMedium·Site Reliability Engineer
  SQL: count files where bull and bear appear as standalone space-delimited words

  SQL practice question: given a table of files and their text content, count how many files contain the words bull and bear as standalone, space-delimited words. It tests careful pattern matching, case sensitivity, NULL handling, and returning a row for each word even when its count is zero.

  Data Manipulation (SQL/Python)Onsite