Data Manipulation (SQL/Python) Interview Questions

Showing 91–120 of 134 results

• 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
  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·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
• MotiveMedium·Software Engineer
  Fetch and parse JSON from REST API

  A Motive Software Engineer onsite coding exercise: build a small, resilient script from scratch that performs an authenticated HTTP GET against a paginated REST API, parses the JSON, extracts and transforms records, and produces both serialized CSV/JSON output and per-category top-k aggregates. It evaluates HTTP/REST integration, rate-limit and retry handling with backoff, timeouts, malformed-record handling, unit testing, logging, and complexity analysis.

  Data Manipulation (SQL/Python)Onsite
• NVIDIAMedium·Software Engineer
  Analyze and debug Python utilities

  This interview question evaluates SQL or pandas logic, joins, grouping, window functions, null handling, edge cases, and validation in a realistic interview setting. A strong answer for Analyze and debug Python utilities states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Data Manipulation (SQL/Python)Onsite
• NetflixMedium·Data Scientist
  Aggregate D1 retention cohorts in SQL

  This question evaluates a candidate's competency in time-series cohort analysis and SQL-based data manipulation, specifically measuring DAU, new-user cohorts, D1 retention and revenue-per-user while handling deduplication and user filtering.

  Data Manipulation (SQL/Python)Onsite
• NetflixMedium·Data Scientist
  Determine Maximum Consecutive Order Days Per User

  Determine Maximum Consecutive Order Days Per User evaluates SQL or pandas logic, joins, grouping, window functions, null handling, edge cases, and validation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Data Manipulation (SQL/Python)Onsite
• NetflixMedium·Data Scientist
  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.

  Data Manipulation (SQL/Python)Onsite
• OpenAIMedium·Machine Learning Engineer
  Implement vectorized NumPy ops and explain broadcasting

  This question evaluates proficiency in vectorized numerical computing with NumPy, understanding of broadcasting semantics, and awareness of numerical stability and algorithmic time/space complexity when manipulating high-dimensional arrays.

  Data Manipulation (SQL/Python)Onsite
• OracleMedium·Software Engineer
  Parse logs and query by time

  This question evaluates competency in parsing and structuring log lines, interpreting timestamps and time zones, handling malformed input, designing insert/query APIs, reasoning about scalability and indexing, performing time/space complexity analysis, and planning basic tests.

  Data Manipulation (SQL/Python)Onsite
• OracleMedium·Software Engineer
  Rank Departments by Student Count

  Tests SQL proficiency in outer joins, aggregation with null handling, and deterministic multi-column sorting.

  Data Manipulation (SQL/Python)Onsitesqlleft-joingroup-by
• PayPalMedium·Data Scientist
  Clean and Summarize User Purchase Data Efficiently

  This question evaluates proficiency in data cleaning, aggregation, and time-series manipulation within the Data Manipulation (SQL/Python) domain, focusing on filtering by group counts and calculating inter-event timing metrics.

  Data Manipulation (SQL/Python)Onsite
• PayPalMedium·Data Scientist
  Compare WHERE vs HAVING with aggregates

  Compare WHERE vs HAVING with aggregates evaluates SQL or pandas logic, joins, grouping, window functions, null handling, edge cases, and validation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Data Manipulation (SQL/Python)Onsite
• PayPalMedium·Data Scientist
  Explain Window Functions and Joins in SQL and Python

  This question evaluates proficiency in SQL and Python data manipulation, covering window functions, join semantics (INNER, LEFT, RIGHT, FULL, CROSS), ranking functions, group and string aggregation, type casting, and building row-wise accumulations in Python, and it falls under the Data Manipulation (SQL/Python) category.

  Data Manipulation (SQL/Python)Onsite
• PayPalMedium·Data Scientist
  Identify Session with Maximum Overlapping Sessions Count

  This question evaluates temporal interval reasoning, set-based querying and aggregation skills, focusing on identifying and counting overlapping time intervals using SQL or equivalent Python data-manipulation tools.

  Data Manipulation (SQL/Python)Onsite
• PayPalMedium·Data Scientist
  Identify Users with Specific Page Visit Sequence

  This question evaluates event-sequence detection and temporal ordering skills in SQL, focusing on concepts such as windowing, adjacent-row reasoning, and session-scoped grouping to identify ordered page visits.

  Data Manipulation (SQL/Python)Onsite
• PayPalMedium·Data Scientist
  Write conditional aggregates with CASE WHEN

  Write conditional aggregates with CASE WHEN evaluates SQL or pandas logic, joins, grouping, window functions, null handling, edge cases, and validation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Data Manipulation (SQL/Python)Onsite
• PayPalMedium·Data Scientist
  Write conditional aggregation SQL queries

  This question evaluates proficiency with conditional aggregation in SQL, including the use of SUM(CASE WHEN ...) versus filtering with WHERE and the implications of placing aggregation filters in HAVING for grouped queries, within the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Analyze Global Engagement and Impressions with SQL Queries

  This question evaluates proficiency in SQL-based data manipulation and analytical querying, covering aggregation, grouping, ranking, and the correlation of impressions with user engagement and feature usage metrics.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Clean and Aggregate Transactions for Finance Dashboard

  This question evaluates data cleaning and transformation competencies including pandas-based vectorized operations, categorical mapping and feature flagging, as well as aggregation and summarization of transactional data in the data manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Implement Binary Search for Policy Violation Logs

  This question evaluates understanding of algorithmic search and data manipulation skills, specifically applying binary search over date-ordered logs and composing efficient queries using SQL and Python.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Transform nested dicts with pandas apply/lambda

  This question evaluates proficiency in pandas-based data manipulation, including flattening nested list and dict structures, parsing nested attributes, computing per-user aggregates and segment metrics, and implementing robust, vectorized extraction logic that handles missing keys and avoids SettingWithCopy pitfalls.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Write SQL to compute max-overlap lists

  This question evaluates proficiency in SQL data manipulation and set-based operations, focusing on deduplication, pairwise aggregation, and similarity metric computation (Jaccard) over relational tables.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Write SQL to rank categories by impressions

  This question evaluates proficiency in SQL data manipulation—covering joins, aggregations, grouping, tie-breaking, date-window logic, and scalability considerations such as indexing and query performance—in the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Write windowed retention and ARPU SQL

  This question evaluates proficiency with SQL window functions, joins, aggregations and time-windowed analytics for computing retention and ARPU, as well as handling date truncation, UTC day boundaries and common data edge cases across user, session, and order tables.

  Data Manipulation (SQL/Python)Onsite
• RobinhoodMedium·Data Scientist
  Create OHLC Aggregates from Tick Data in Python

  This question evaluates a candidate's ability to perform time-series bucketing and OHLC aggregation from tick data, testing skills in data parsing, stateful aggregation, and handling missing-interval forward-filling; it falls under Data Manipulation (SQL/Python) and assesses practical application rather than purely conceptual understanding.

  Data Manipulation (SQL/Python)Onsite
• RobloxMedium·Data Scientist
  Analyze Recent Orders Dataset with Python/pandas

  This question evaluates proficiency in data manipulation and aggregation using Python/pandas, including extracting per-user maximums, computing overall summary statistics, and producing daily aggregates from time-stamped records.

  Data Manipulation (SQL/Python)Onsite
• RobloxMedium·Data Scientist
  Generate Friendship List with Acceptance Dates Using Pandas

  This question evaluates proficiency in data manipulation and relational reasoning using Python/pandas, focusing on transforming event logs into canonical pairwise relationships and extracting activation timestamps.

  Data Manipulation (SQL/Python)Onsite
• RobloxMedium·Data Scientist
  Match requests and accepts into friendships in SQL

  This question evaluates a candidate's competency in SQL data manipulation, focusing on temporal joins, deduplication of bidirectional relationships, selecting the earliest valid event, and reasoning about event-order constraints.

  Data Manipulation (SQL/Python)Onsite
• SScribdMedium·Software Engineer
  Many-to-Many Schema Design With a Join Table, Composite Primary Key, and Queries

  Design a relational schema modeling a many-to-many relationship between documents and tags using a join table with a composite primary key, index both lookup directions, and write queries handling outer joins and relational division.

  Data Manipulation (SQL/Python)OnsiteSQLDatabase DesignPostgreSQL