Data Manipulation (SQL/Python) Interview Questions

Showing 1–30 of 446 results

• AdobeMedium·Software Engineer
  Find Top-Funded Villages and Their Top Projects

  Tests the ability to write a multi-level SQL aggregation with window functions, exact date filtering, tie handling, and deterministic sorting.

  Data Manipulation (SQL/Python)Online Assessmentsqlwindow-functionsaggregation
• AdobeMedium·Software Engineer
  Implement scalable word count locally

  This question evaluates understanding of scalable word-count processing, including tokenization and normalization rules, streaming or external-memory techniques for inputs larger than RAM, and efficient top‑K frequency computation.

  Data Manipulation (SQL/Python)Technical Screen
• AdobeMedium·Data Scientist
  Solve SQL and Python Data Manipulation Tasks

  This question evaluates proficiency in SQL event-log aggregation and basic Python data-structure transformations, assessing competencies such as counting distinct users, identifying frequent event types, and performing dictionary/list/string manipulations.

  Data Manipulation (SQL/Python)Onsite
• AAeoneaMedium·Software Engineer
  Fill missing values with means

  This question evaluates proficiency in missing-data imputation and pandas DataFrame manipulation, testing skills in column-wise aggregation, group-wise operations, and edge-case handling within the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Technical Screen
• AffirmMedium·Data Scientist
  Analyze Loan Payments Using Pandas for Key Insights

  This question evaluates data manipulation and aggregation skills using pandas, focusing on computing per-loan payment totals, payment success rates, and a repayment-status flag. It is commonly asked to assess applied data wrangling and numeric summarization abilities in the Data Manipulation (SQL/Python) domain, testing practical application rather than purely conceptual understanding.

  Data Manipulation (SQL/Python)Technical Screen
• AffirmMedium·Software Engineer
  Analyze Returning Borrowers Across Two Days of Logs

  Process two daily loan activity logs to identify users active on both days with diverse loan types, then score them using a configurable trust policy.

  Data Manipulation (SQL/Python)Technical ScreenData ManipulationHash TablePython
• AffirmMedium·Software Engineer
  Implement and debug event filtering in Python

  This question evaluates proficiency in data manipulation and algorithmic reasoning in Python, covering event filtering, stable sorting, deduplication by identifier, timestamp windowing, and analysis of time and space complexity.

  Data Manipulation (SQL/Python)Onsite
• AgodaEasy·Data Engineer
  Find the Longest Calendar-Day Streak with All Employees Present

  Identify dates when every employee is present and compute the longest consecutive streak, treating missing attendance as a gap.

  Data Manipulation (SQL/Python)Technical Screen
• AgodaEasy·Data Engineer
  Rank Customers by Monthly Revenue with Competition Ties

  Aggregate customer revenue by month and return top competition ranks, preserving tied totals and deterministic display order.

  Data Manipulation (SQL/Python)Technical Screen
• AgodaEasy·Data Engineer
  Return Every Employee with a Mapped or Default Unique ID

  Join employees to unique-ID mappings while preserving unmatched employees and applying an explicit fallback identifier.

  Data Manipulation (SQL/Python)Technical Screen
• AirbnbMedium·Data Scientist
  Aggregate User Activity, Fit Regression, Interpret Coefficients

  This question evaluates skills in relational data aggregation and feature engineering using SQL alongside fitting and interpreting regression models in Python, targeting competencies in transforming event-level user metrics into a modeling dataset and interpreting coefficient estimates.

  Data Manipulation (SQL/Python)Technical Screen
• AirbnbMedium·Data Scientist
  Build panel in SQL; run causal regression

  This question evaluates proficiency in SQL-based panel data construction, time-series aggregation and rolling-window metrics together with applied causal inference in Python, including two-way fixed-effects difference-in-differences, clustered standard errors, lead tests, and count-model re-specification; it targets Data Manipulation (SQL/Python) skills relevant for Data Scientist roles. It is commonly asked because it combines practical implementation and conceptual understanding—testing temporal joins, treatment timing, avoidance of lookahead/immortal-time biases and late-adopter issues, interpretation of interaction coefficients and confidence intervals, and the ability to reason about identification and model choice.

  Data Manipulation (SQL/Python)Technical Screen
• AirbnbMedium·Data Engineer
  Calculate the Median House Price in Each City

  Tests your ability to compute grouped medians in PostgreSQL, properly handling even and odd row counts, duplicate price values, and numeric precision.

  Data Manipulation (SQL/Python)Onsitesqlpostgresqlaggregations
• AirbnbMedium·Data Scientist
  Compute C/T metrics from bookings and visits

  This question evaluates time-window attribution, visit deduplication, control vs treatment metric computation, aggregation of conversions and revenue, and statistical interval estimation (Wilson CIs), testing practical data manipulation skills with SQL or Python in the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Technical Screen
• AirbnbMedium·Data Scientist
  Compute browsing metrics in Python from logs

  This question evaluates a candidate's ability to perform event-level data manipulation and analytics in Python and SQL, covering sessionization, time-zone–consistent timestamp handling, deduplication, funnel construction, segment-level aggregation, conversion-rate computation, and statistical confidence intervals such as the Wilson CI.

  Data Manipulation (SQL/Python)Technical Screen
• AirbnbMedium·Data Scientist
  Describe How You Use SQL in Data Science Work

  This question assesses a candidate's ability to articulate their technical workflow in SQL, focusing on data extraction strategies, quality assurance, and how technical analysis translates into business impact.

  Data Manipulation (SQL/Python)HR ScreenSQLData ScienceAnalytics
• AirbnbMedium·Data Engineer
  Estimate Page-Visit Duration from the Next User Event

  Implement logic to compute user page-visit durations based on adjacent event timestamps, deterministically resolving ties and handling boundary conditions for terminal events.

  Data Manipulation (SQL/Python)Onsitepythonsqldata-manipulation
• AirbnbMedium·Data Engineer
  Find Hosts Meeting Listing, Rating, and Review-Coverage Rules

  Tests the ability to write a SQL query performing multi-table aggregations, date-windowed conditional logic, and host-level qualification filtering across listing counts, average ratings, and recent review coverage.

  Data Manipulation (SQL/Python)Onsitesqlaggregationconditional-logic
• AirbnbMedium·Data Engineer
  Find Users with Seven Consecutive Impression Days

  Tests your ability to identify consecutive calendar-day activity streaks in PostgreSQL using window functions, date arithmetic, and deduplication.

  Data Manipulation (SQL/Python)Onsitesqlpostgresqlwindow-functions
• AirbnbMedium·Software Engineer
  Review a geospatial Python module

  This question evaluates proficiency in geospatial data processing and Python code review, including detection of correctness bugs, numerical stability issues, CRS handling, performance optimization, refactoring, testing strategy, and security considerations when working with CSV/GeoJSON datasets.

  Data Manipulation (SQL/Python)Technical Screen
• AirwallexMedium·Data Scientist
  Compute Moderation View Metrics

  An Airwallex Data Scientist onsite SQL question on content-moderation analytics. You write three queries over a per-day view table and a one-to-many post/violation-type policy-score table: distinct posts with 10+ views in the last 7 days, Nudity view prevalence over the last 30 days, and a monthly violation-type distribution. The core challenge is windowed aggregation plus avoiding view double-counting across violation types.

  Data Manipulation (SQL/Python)Onsite
• Akuna CapitalMedium·Software Engineer
  Answer SQL MCQs with reasoning

  This question evaluates proficiency in SQL query semantics and reasoning about relational operations—specifically INNER, LEFT, and RIGHT JOIN behavior; GROUP BY and HAVING usage; NULL handling in comparisons and aggregates; window functions such as ROW_NUMBER and RANK; and the logical query processing order—within the Data Manipulation (SQL/Python) domain. It is commonly asked to assess the ability to interpret and justify query outcomes versus alternative answers, testing both conceptual understanding of relational theory and practical application of SQL query behavior.

  Data Manipulation (SQL/Python)Online Assessment
• Akuna CapitalMedium·Software Engineer
  Evaluate SQL expressions for zero

  This question evaluates understanding of SQL type coercion, boolean semantics, comparison operators, and dialect-specific evaluation behavior (for example, MySQL), focusing on interpreting expressions that may evaluate to zero.

  Data Manipulation (SQL/Python)Online Assessment
• AmazonMedium·Business Intelligence Engineer
  Analyze Seller Compliance and Customer Purchase Patterns

  This question evaluates a candidate's ability to manipulate and analyze temporal and categorical datasets, covering competencies such as event sequencing, set-based filtering, and cross-table aggregation in SQL/Python.

  Data Manipulation (SQL/Python)Onsite
• AmazonMedium·Data Scientist
  Analyze Top 10 Items' Revenue Contribution by Category

  This question evaluates proficiency in data manipulation and analytical querying—aggregation, window functions, ranking and revenue attribution—alongside conceptual knowledge of normalization versus denormalization and ETL pipeline design.

  Data Manipulation (SQL/Python)Onsite
• AmazonMedium·Data Scientist
  Append country tables and rank salaries in USD

  This question evaluates skills in data manipulation and integration, specifically appending country-level tables, normalizing salaries via historical exchange rates, deduplicating by a composite primary key, and ranking results, with implementations expected in both SQL and pandas.

  Data Manipulation (SQL/Python)Technical Screen
• AmazonMedium·Data Scientist
  Build DID panel and compute effects in SQL

  This question evaluates proficiency in panel data construction and causal inference workflows, specifically difference-in-differences estimation, SQL aggregation for user-week metrics, and propensity-score matching implemented in Python.

  Data Manipulation (SQL/Python)HR Screen
• AmazonMedium·Data Scientist
  Build DiD dataset with SQL

  This question evaluates proficiency in SQL-based data manipulation and panel construction for staggered-adoption difference-in-differences, testing skills in handling adoption dates, event-time calculations, boundary conditions, and aggregation in the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Technical Screen
• AmazonMedium·Data Scientist
  Calculate Defect Rate and Identify Top Lanes for Carriers

  This question evaluates competency in SQL-based data manipulation for a data scientist role, covering joins, aggregations, date-based filtering, metric computation, and use of window functions to derive week-over-week changes.

  Data Manipulation (SQL/Python)Technical Screen
• AmazonMedium·Data Scientist
  Calculate Monthly Revenue from Orders in 2023

  This question evaluates proficiency in SQL-based data manipulation, including aggregation, date extraction, and combining transactional tables to produce business metrics, and falls under the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Technical Screen