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Coding questions
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Coding questions · Capital One
Write SQL for lowest price with ratings
This question evaluates SQL data-manipulation skills including aggregation, conditional filtering, NULL handling, grouping, and deterministic ordering, and sits in the Data Manipulation (SQL/Python) domain with an emphasis on practical application of query writing rather than purely conceptual design.
Coding questions · Chime
Write SQL for noisy A/B launch metrics
This question evaluates SQL-based data manipulation and experimental analytics skills, including attribution of earliest exposures, censoring crossovers, session-based bot qualification, time-windowed conversion and revenue calculations, and exclusion of outage periods in PostgreSQL.
Coding questions · DoorDash
Write SQL for percent and window changes
This question evaluates proficiency with advanced SQL techniques—specifically the use of CTEs and multiple window functions, row-level versus aggregated conditionals, time-windowed aggregations, generation of unit-day series including zero-order days, and correct handling of missing exposure labels for percent and change calculations.
Coding questions · Meta
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.
Coding questions · Point72
Write SQL for recent customer activity
This question evaluates SQL data-manipulation and analytics competencies including joining and filtering multiple tables, time-windowed aggregations, distinct counts, monetary aggregation with refunds, and handling status-based inclusion and edge cases.
Coding questions · Meta
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.
Coding questions · Meta
Write SQL for revenue and advertiser analyses
This question evaluates a candidate's proficiency in SQL data manipulation and analytics, including aggregation, joins, date-range filtering, handling missing-period values, distinct counts, and proportional calculations within the Data Manipulation (SQL/Python) domain.
Coding questions · Wells Fargo
Write SQL for rolling default rates
This question evaluates proficiency with SQL window functions and time-series aggregation, specifically the ability to compute rolling metrics across customer segments by aggregating defaults and accounts over a moving 12-month window.
Coding questions · Netflix
Write SQL for rolling frequency caps
This question evaluates proficiency with rolling-window analytics, frequency cap logic, time-based attribution, and per-user/per-campaign aggregation for advertising data.
Coding questions · Meta
Write SQL for shop visibility and activity metric
This question evaluates SQL-based data manipulation and analytical skills, including aggregations, window functions, cohort comparisons, ranking, median calculation with analytic functions, and careful handling of NULLs versus zeros when constructing time-windowed metrics like visibility_rate and activity_score.
Coding questions · Stripe
Write SQL for snapshot features and labels
This question evaluates proficiency in SQL-based feature engineering for time-series and user-event data, covering snapshotting, temporal joins, deduplication, windowed aggregations, distinct counting, and label construction in the Data Manipulation (SQL/Python) domain.
Coding questions · Meta
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.
Coding questions · HBO
Write SQL for streaming cohort metrics
This question evaluates proficiency in SQL-based data manipulation and analytics, focusing on cohort analysis, temporal filtering, aggregation, deduplication and experiment metric computation within the Data Manipulation (SQL/Python) domain and the ability to translate business metric definitions into queryable datasets.
Coding questions · Capital One
Write SQL for theme-park revenue and visits
This question evaluates SQL data-manipulation and analytical skills, including joins, aggregations, date-range filtering, handling multiple ticket ownership, and edge cases like zero counts when computing revenue and visit metrics.
Coding questions · TikTok
Write SQL for TikTok Live creator metrics
This question evaluates SQL data-manipulation competencies such as joins, aggregations, group-by and window functions, handling missing activity rows, date-range filtering, country partitioning, and deterministic tie-breaking for top-k metrics.
Coding questions · Point72
Write SQL for top student per department
This question evaluates proficiency in SQL query formulation, including group-wise selection, joins, NULL handling, deterministic tie-breaking and ordering to identify a top-per-group student.
Coding questions · Meta
Write SQL for visibility, calls, and cohort activity
This question evaluates a candidate's proficiency in SQL-based data manipulation, covering aggregations, joins, window functions, date arithmetic, deduplication, cohorting, and calculation of engagement metrics.
Coding questions · Meta
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.
Coding questions · Gemini
Write SQL/Python for ACH fraud analytics
This question evaluates time-windowed analytics, SQL window functions and joins, ranking and event correlation, streaming de-duplication in Python, and domain knowledge of ACH payment and return behaviors within the Data Manipulation (SQL/Python) category.
Coding questions · Uber
Write SQL/Python for CTR analytics
This question evaluates proficiency in data manipulation and analytics, covering SQL windowing and deduplication for time‑windowed cohort metrics (48‑hour unique CTR) as well as practical Python model evaluation tasks such as precision‑recall plotting, weighted F1 threshold selection, and precision@top‑k.
Coding questions · Coinbase
Write SQL: sum values ≤ each row’s value
This question evaluates proficiency in SQL aggregation, query optimization, and handling duplicate values when computing cumulative sums across rows. It is commonly asked to assess practical ability in the Data Manipulation (SQL/Python) domain to design scalable, efficient queries and demonstrates a focus on practical application of query-design and optimization rather than purely conceptual theory.
Coding questions · Meta
Write SQL to analyze group-call concurrency
This question evaluates advanced SQL competency in temporal interval analysis, concurrency counting, percentile aggregation, and complex user-filtering logic, testing skills in data manipulation, analytic/window functions, and performance-aware querying.
Coding questions · Meta
Write SQL to analyze Group Calls adoption
This question evaluates SQL-based data manipulation and experiment analysis skills, including cohort selection, time-window filtering, joins, aggregations, and difference-in-differences style comparisons using a PostgreSQL event schema.
Coding questions
Write SQL to analyze response accuracy and speed
This question evaluates proficiency with SQL-based data manipulation and analytical querying on relational assessment data, including aggregation, grouping, joins, windowed ranking, and use of PostgreSQL statistical functions to analyze accuracy and response-time metrics.