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Data Manipulation (SQL/Python) Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
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Showing 1–30 of 134 results
- AdobeMediumData ScientistSolve 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 - AffirmMediumSoftware EngineerImplement 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 - AirbnbMediumData EngineerCalculate 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 - AirbnbMediumData EngineerEstimate 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 - AirbnbMediumData EngineerFind 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 - AirbnbMediumData EngineerFind 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 - AirwallexMediumData ScientistCompute 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 - AmazonMediumBusiness Intelligence EngineerAnalyze 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 - AmazonMediumData ScientistAnalyze 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 - AmazonMediumBusiness Intelligence EngineerCalculate Rolling 7-Day Sum of Answers by Device
This question evaluates proficiency in time-series aggregation and group-wise metric computation on structured data, specifically calculating rolling seven-day sums of answers per device, and assesses familiarity with data manipulation using SQL or Python.
Data Manipulation (SQL/Python)Onsite - AmazonMediumBusiness Intelligence EngineerCompute First Order Proportions by Day and Category
This question evaluates a candidate's ability to perform event-level data manipulation and customer-level deduplication using SQL or Python, focusing on calculating the proportion of orders that represent a customer's first purchase by day and category.
Data Manipulation (SQL/Python)Onsite - AmazonMediumData ScientistCompute daily work hours from in/out events
This question evaluates a candidate's ability to manipulate time-series punch-event data, including temporal pairing of in/out events, splitting shifts across calendar days, rounding and aggregating hours, and detecting data-quality issues such as overlaps or orphaned events using SQL or Python.
Data Manipulation (SQL/Python)Onsite - AmazonMediumData ScientistCompute join counts and window ranks
This question evaluates SQL data-manipulation and analytic competencies including join semantics, set operations, window functions, view versus materialized view trade-offs, key and partition design, and query-tuning techniques in the Data Manipulation (SQL/Python) domain.
Data Manipulation (SQL/Python)Onsite - AmazonMediumBusiness Intelligence EngineerCount Customers Buying Both 'Kindle' and 'Alexa'
This question evaluates proficiency in relational data manipulation and set-based reasoning, assessing SQL competency such as joins, aggregation, and identifying distinct customers who purchased multiple specified products.
Data Manipulation (SQL/Python)Onsite - AmazonMediumData ScientistDesign student–course data models and SQL
This question evaluates data modeling, database design, and SQL proficiency—covering normalization, schema constraints, indexing, star-schema warehousing, slowly changing dimensions, partitioning strategies, and complex analytic queries—in the domain of relational databases and data warehousing (Data Manipulation/SQL).
Data Manipulation (SQL/Python)Onsite - AmazonMediumBusiness Intelligence EngineerFind Top Three Books by City in Recent Months
This question evaluates proficiency in time-windowed aggregation, group-level ranking and window-function usage on relational datasets, emphasizing handling of recent date ranges and top-N selection.
Data Manipulation (SQL/Python)Onsite - AmazonMediumData ScientistFind Top-3 Salaries Per Department Using SQL
This question evaluates SQL data manipulation competency, focusing on group-wise aggregation, ordering, and selecting the top-N salary values within each department.
Data Manipulation (SQL/Python)Onsite - AmazonMediumData ScientistFind top-spend categories per customer with ranking
This question evaluates proficiency with SQL aggregation and JOINs, analytic/window functions (RANK()), tie and NULL/edge-case handling, and percent-of-total calculations for per-customer spend analysis.
Data Manipulation (SQL/Python)Onsite - AmazonMediumData ScientistIdentify First Daily Order for Each Merchant
This question evaluates proficiency in data manipulation with SQL and related tools, focusing on identifying the first transaction per merchant for each calendar date and handling ordering and deduplication within grouped transactional records.
Data Manipulation (SQL/Python)Onsite - AmazonMediumBusiness Intelligence EngineerIdentify Most Popular First-Watched Movie in Viewing History
This question evaluates proficiency in data manipulation and temporal event analysis, assessing competency in identifying per-user earliest views and aggregating frequencies using SQL or Python.
Data Manipulation (SQL/Python)Onsite - AmazonMediumBusiness Intelligence EngineerIdentify Top-Buying Customers Daily with SQL Query
This question evaluates a candidate's competency in SQL data manipulation, including aggregation over calendar dates, grouping by customer, and handling ties when determining top buyers.
Data Manipulation (SQL/Python)Onsite - AmazonMediumBusiness Intelligence EngineerIdentify Unique Unordered City Pairs in Flight Log
This question evaluates competency in data manipulation, deduplication of symmetric relationships, and handling unordered pairs within relational or tabular datasets using SQL or Python/Pandas.
Data Manipulation (SQL/Python)Onsite - AmazonMediumBusiness Intelligence EngineerIllustrate SQL Join Results with Duplicate Keys
This question evaluates understanding of SQL join semantics and the effect of duplicate key values on result cardinality, assessing competency in relational data manipulation and reasoning about result sets.
Data Manipulation (SQL/Python)Onsite - AmazonMediumData ScientistTransform event logs with subscription windows in pandas
This question evaluates a candidate's competency in time-based event attribution and temporal interval manipulation using pandas, covering interval merging, subscription-aligned revenue aggregation, anomaly flagging, and handling edge cases like overlapping or back-to-back subscriptions.
Data Manipulation (SQL/Python)Onsite - AppleEasyData ScientistWrite queries to compute salary and budget stats
This set of tasks evaluates data manipulation and analytical competencies, specifically the ability to compute order-statistics on numeric columns, perform relational joins to enrich event records, and reason about constrained selection for maximizing hires using SQL and pandas.
Data Manipulation (SQL/Python)Onsite - Applied IntuitionMediumSoftware EngineerImplement a nested object validator
This question evaluates proficiency in nested data validation, schema interpretation, and type checking for hierarchical objects, including handling nulls, arrays, extra fields, and clear error reporting.
Data Manipulation (SQL/Python)Onsite - Capital OneMediumData ScientistAudit flight data quality from metadata
This question evaluates data quality auditing competencies, including validation of timestamps and timezones, detection of label leakage and inconsistent units, provenance and schema enforcement, and hands‑on use of SQL/Python for dataset inspection.
Data Manipulation (SQL/Python)Onsite - Capital OneEasyData ScientistClean and Merge Housing Data
This question tests the ability to clean messy housing datasets, handle inconsistent data types, and perform efficient left-joins with external reference data.
Data Manipulation (SQL/Python)OnsitePandasData CleaningSQL - Capital OneMediumData ScientistCompute Customer Spend and Engineer Features for 2023
This question evaluates proficiency in SQL-based temporal aggregation and Python feature engineering on transactional datasets, including computing monthly spend summaries and engineering category-level spending features.
Data Manipulation (SQL/Python)Onsite - Capital OneMediumData ScientistDetermine Country with Most 'Sunny' Days
This question evaluates proficiency in data aggregation, grouping, and filtering to summarize categorical time-series records using SQL or equivalent Python data-manipulation tools, and it belongs to the Data Manipulation domain with an emphasis on practical application of query and aggregation techniques.
Data Manipulation (SQL/Python)Onsite
Adobe
Affirm
Airbnb
Airwallex
Amazon
Apple
Applied Intuition
Capital One