Data Manipulation (SQL/Python) interview questions

Showing 391–420 of 446 results

• Compute weekly 3-week rolling sums in SQLMedium

  This question evaluates time zone–aware date bucketing, gapless calendar generation, and rolling-window aggregation skills, demonstrating competency in SQL-based data manipulation and temporal reasoning.

  ThumbtackData ScientistData Manipulation (SQL/Python)HR Screen
• Compute weighted response rates by job categoryMedium

  This question evaluates a candidate's data manipulation and statistical estimation skills, including pandas-based aggregation, invitation-weighted rate calculation, confidence-interval computation, and robust handling of data-quality issues, in the Data Manipulation (SQL/Python) domain.

  ThumbtackData ScientistData Manipulation (SQL/Python)Onsite
• Calculate Conversion Rate from Ad Clicks to Page VisitsMedium

  This question evaluates a candidate's competency in event-level data manipulation and metric computation using SQL or Python, including time-based aggregation, deduplication, and joining or windowing of event streams.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Calculate Day-7 Retention Rate from User Post DataMedium

  This question evaluates a candidate's competency in SQL and Python data wrangling, emphasizing date arithmetic, window functions, grouping, and conditional aggregation for cohort and retention calculations.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Calculate User Registration Date and 7-Day Retention RateMedium

  This question evaluates the ability to perform time-based data manipulation and cohort retention analysis using SQL/Python, including deriving registration dates, aggregating posts within time windows, and computing retention metrics.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Calculate valid daily usage with gap constraintsMedium

  This question evaluates a candidate's ability to manipulate temporal intervals, including clipping to a specified day window, merging touching or overlapping segments, detecting gaps, and aggregating minute-level durations using SQL window functions and date/time arithmetic, and belongs to the Data Manipulation (SQL/Python) domain.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Compute 7-day rolling complaint/order ratio in SQLMedium

  This question evaluates SQL data manipulation skills, specifically time-based aggregations, sliding window functions, joins to include entities with no events, and numeric casting within the Data Manipulation (SQL/Python) domain.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Compute CTR drop with exclusionsMedium

  This question evaluates a candidate's ability to compute time-windowed click-through rates using SQL aggregations, joins, filters and data-cleaning (excluding suspicious ads) while handling edge cases such as missing days, minimum-impression thresholds, division-by-zero, and integer-division pitfalls.

  TikTokData ScientistData Manipulation (SQL/Python)Onsite
• Compute and rank top bad advertisersMedium

  This question evaluates proficiency in SQL data manipulation and analytics, including time-window filtering, JOINs, aggregation and deduplication, rate calculations, and window-function–based ranking.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Compute last-to-previous ad impression gapsMedium

  This question evaluates proficiency in data manipulation and time-based analytics, covering SQL window functions, timestamp arithmetic, and grouping/ordering semantics within the Data Manipulation (SQL/Python) domain.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Count buggy vs non-buggy by employerMedium

  This question evaluates proficiency in SQL data manipulation—particularly conditional aggregation and join semantics—for counting categorized records across related tables in a data science context.

  TikTokData ScientistData Manipulation (SQL/Python)Online Assessment
• Debug a Hive Query for DAUMedium

  This question evaluates proficiency in Hive/SQL query formulation, data partitioning and pruning, join and aggregation semantics, timestamp handling, and performance tuning for large-scale analytics.

  TikTokData EngineerData Manipulation (SQL/Python)Technical Screen
• Debug a Hive insert queryMedium

  This question evaluates a candidate's ability to debug Hive INSERT/SELECT operations, focusing on schema and column alignment, data types and casts, partition handling, file formats/SerDe, ACID/transactional constraints, and syntax or reserved keyword issues.

  TikTokData EngineerData Manipulation (SQL/Python)Technical Screen
• Discuss Python mutability, copying, and GILMedium

  This question evaluates understanding of Python mutability and copying semantics — including how mutable versus immutable objects affect function arguments and container behavior — and knowledge of the Global Interpreter Lock (GIL) and concurrency models.

  TikTokSoftware EngineerData Manipulation (SQL/Python)Technical Screen
• Explain a SQL query resultMedium

  This question evaluates proficiency in SQL result-set interpretation and reasoning about joins, filters, aggregations, window functions, NULL handling, duplicate rows, and ordering within the Data Manipulation (SQL/Python) domain for a Data Engineer role.

  TikTokData EngineerData Manipulation (SQL/Python)Technical Screen
• Find top-paid employee per departmentEasy

  This question evaluates a candidate's competency in SQL data manipulation, including aggregation, ranking, handling of duplicate and historical rows, tie semantics, and temporal data interpretation when determining the top-paid employee per department.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Identify Repeat Advertisers from Consecutive WeeksMedium

  This question evaluates a candidate's proficiency in manipulating relational data to identify recurring entities across consecutive time periods, focusing on SQL/Python data manipulation and temporal comparison of records.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Investigating Correlation Between Ad Visits and ReportsMedium

  This question evaluates a data scientist's competency in operational analytics, including defining and aggregating metrics in SQL and applying causal reasoning to interpret correlations between ad exposures and user reports.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• SQL Queries and Analysis on Bad AdvertisersMedium

  This question evaluates SQL query writing, metric definition and normalization, ranking/aggregation techniques, and analytical reasoning for identifying problematic advertisers.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Select max-discount product per categoryMedium

  This question evaluates proficiency in data manipulation and SQL querying—specifically use of window functions versus set-based alternatives, group-level ranking and tie-breaking, NULL-aware expressions, and numeric precision when computing discounts within the Data Manipulation (SQL/Python) domain.

  TikTokData ScientistData Manipulation (SQL/Python)Online Assessment
• Write SQL for 7-day geo-localized revenue dashboardMedium

  This question evaluates SQL skills in time-zone aware local-date aggregation, idempotent event deduplication, cohorting for new versus returning users, calculation of revenue and conversion metrics, and anomaly detection via median-based drop flags.

  TikTokData ScientistData Manipulation (SQL/Python)HR Screen
• Write SQL for TikTok Live creator metricsEasy

  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.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Write SQL for geo posting-frequency dropsMedium

  This question evaluates proficiency in SQL-based time-series data manipulation, including time zone–aware date normalization, window functions, aggregation, filtering and median computations within the Data Manipulation (SQL/Python) domain.

  TikTokData ScientistData Manipulation (SQL/Python)Onsite
• Write SQL for last-7-day metrics without windowsMedium

  This question evaluates proficiency in ANSI SQL data manipulation, including aggregation, de-duplication, date arithmetic, joins and subqueries, GROUP BY/HAVING usage, and cohort/retention and conversion calculations performed without window functions.

  TikTokData ScientistData Manipulation (SQL/Python)Technical Screen
• Write complex SQL for cohorts and retentionMedium

  This question evaluates advanced SQL and data-engineering competencies such as cohort and retention analysis, deduplication, timezone normalization, last-touch attribution, aggregate revenue calculations, and effective use of window functions in the Data Manipulation (SQL/Python) domain.

  TikTokSoftware EngineerData Manipulation (SQL/Python)Technical Screen
• Compute reply-based engagement metricsEasy

  This question evaluates proficiency in data manipulation and analytics, emphasizing SQL/Python skills for temporal filtering, joins between posts and users, deduplication, aggregation (distinct counts), and percentage calculations used to compute reply-based engagement metrics.

  Tools For HumanityData ScientistData Manipulation (SQL/Python)Technical Screen
• Compute daily net users from event logsMedium

  This question evaluates SQL-based data manipulation skills focused on daily aggregation, cohort and retention calculations, deduplicating event records, and grouping metrics by device_platform.

  TubiData ScientistData Manipulation (SQL/Python)Technical Screen
• Analyze Streaming Data with SQL for Monthly TrendsMedium

  This question evaluates proficiency in SQL time-series aggregation, date extraction and grouping across calendar months, join and conditional aggregation techniques, windowed month-over-month comparisons, and handling sparse or multi-year datasets; Category: Data Manipulation (SQL/Python); level: practical application.

  TwitchData ScientistData Manipulation (SQL/Python)Technical Screen
• Solve advanced SQL for streaming analyticsMedium

  This question evaluates advanced SQL competency for streaming analytics — covering time-series aggregation, monthly bucketing across year boundaries, joins between event tables, window functions, and case-insensitive substring filtering; the domain is Data Manipulation (SQL/Python) and the level is practical application of SQL techniques.

  TwitchData ScientistData Manipulation (SQL/Python)Technical Screen
• Analyze NYC taxi trips efficiently over last 7 daysMedium

  This question evaluates proficiency in time-series filtering, relational joins, grouped aggregations (median and high-percentile calculations), numeric stability of percentile methods, and performance-aware vectorized data manipulation using SQL or pandas.

  Two SigmaData ScientistData Manipulation (SQL/Python)Online Assessment