Data Manipulation (SQL/Python) Interview Questions

Showing 121–134 of 134 results

• SScribdMedium·Software Engineer
  Most Popular Actors Query When Object IDs Mix Movies and People With Multiple Roles

  A data query question about ranking the most popular actors when an object ID can refer to either a movie or a person, and one person can hold several roles in the same movie. It tests clarifying the popularity metric, filtering to actor credits, deduplicating person and movie pairs, checking object types, and defining a tie policy.

  Data Manipulation (SQL/Python)Onsite
• ShopifyMedium·Data Scientist
  Determine Growth of Pirated Theme Installations Over Years

  This question evaluates proficiency in SQL-based data manipulation and analytics, focusing on computing time-based cohort percentages and conducting year-over-year trend analysis of merchant behavior.

  Data Manipulation (SQL/Python)Onsite
• SnapchatMedium·Data Scientist
  Compute CTR and metrics with pandas

  This question evaluates proficiency in time-series and event-level data manipulation with pandas, including CTR computation, event denoising and deduplication, sessionization, cohort analysis, temporal joins, and performance-aware vectorized operations within the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Onsite
• SnapchatMedium·Data Scientist
  Compute User Retention and Analyze Event Data

  This question evaluates a candidate's ability to perform SQL and Python data manipulation for event analytics, including cohort retention, aggregation of distinct purchasing users, median-of-daily-events calculations, and hourly time-series grouping.

  Data Manipulation (SQL/Python)Onsite
• SnowflakeMedium·Data Scientist
  Build a cohort dashboard with Streamlit and SQL

  This question evaluates proficiency in cohort analysis using SQL window functions, time-based aggregation, ARPU calculation, and integration of data querying with a Streamlit visualization front end, including handling timezones and data-quality checks.

  Data Manipulation (SQL/Python)Onsite
• SnowflakeMedium·Data Scientist
  Design an analytic warehouse for event data

  This question evaluates a candidate's competency in data warehousing and engineering for analytics, including event-level schema and partitioning, slowly changing dimensions, idempotent ingestion and deduplication, derived metrics modeling, and query performance and cost trade-offs using SQL/Python.

  Data Manipulation (SQL/Python)Onsite
• StripeMedium·Data Scientist
  Write SQL to monitor weekly chargeback spikes

  This question evaluates proficiency in PostgreSQL time-series analytics, specifically aggregations, joins across payments and chargebacks, handling late-arriving events, and calculating per-week metrics such as GMV, active merchants, and chargeback rates.

  Data Manipulation (SQL/Python)Onsite
• ThumbtackMedium·Data Scientist
  Compare list/dict; parse JSON/CSV at scale

  This question evaluates understanding of Python data structures (list vs dict), algorithmic time and memory complexity, ordering guarantees in CPython, large-scale parsing and streaming of JSON/CSV, and robust data-cleaning and error-handling strategies.

  Data Manipulation (SQL/Python)Onsite
• ThumbtackMedium·Data Scientist
  Compute weighted response rates by job category

  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.

  Data Manipulation (SQL/Python)Onsite
• TikTokMedium·Data Scientist
  Compute CTR drop with exclusions

  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.

  Data Manipulation (SQL/Python)Onsite
• TikTokMedium·Data Scientist
  Write SQL for geo posting-frequency drops

  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.

  Data Manipulation (SQL/Python)Onsite
• WaymoEasy·Data Scientist
  Merge overlapping intervals per group in pandas

  This problem tests your ability to handle temporal data by merging overlapping time intervals within distinct groups using pandas and custom logic.

  Data Manipulation (SQL/Python)OnsitePandasData ManipulationIntervals
• WaymoMedium·Data Scientist
  SQL: Average Ride Rating in Users' First and Third Active Months by City

  Write a PostgreSQL query that compares average ride ratings in each user's first and third active months, grouped by city and averaged over individual rides. Tests ranking distinct active months per user, window functions, NULL ratings and weighting.

  Data Manipulation (SQL/Python)Onsite
• WaymoMedium·Data Scientist
  SQL: Users With No Rides in the Most Recent 7-Day Window, Including Non-Riders

  Write a PostgreSQL query that lists users with no rides in the most recent 7-day window, including users who never rode. Tests anchoring a date window to the data, inclusive boundaries, and anti-join logic that keeps users without matching rides.

  Data Manipulation (SQL/Python)Onsite