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Learn/Data Engineering for AI

Course

Data Engineering for AI

The data layer under AI systems: advanced SQL, dimensional modeling, dbt transformations, Spark, orchestration, streaming, and feature stores.

48 practice questions25 free23 company-verified (Pro)

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Course chapters

1
SQL for data & AI
15min · concept, worked example, practice & checkpoint
2
Data modeling
14min · concept, worked example, practice & checkpoint
3
Pipelines & orchestration
14min · concept, worked example, practice & checkpoint
4
Batch & streaming
14min · concept, worked example, practice & checkpoint
5
Warehousing, features & data quality
13min · concept, worked example, practice & checkpoint

Free to practice

Feature Store Architecture for Real-Time Fraud Detection

ML Engineering

easy

Window Functions for Order AnalyticsData Engineeringeasy

Lakehouse Architecture for 50TB of JSON EventsData Engineeringeasy

PostgreSQL Analytics Performance IssueData Engineeringeasy

Joining Postgres, Stripe, and Salesforce for AnalyticsData Engineeringeasy

Random Projection Index for High-Dimensional Nearest Neighbor SearchData Engineeringeasy

RANGE vs ROWS window frames: ROWS uses physical row count, RANGE uses value-based ordering.Data Engineeringeasy

Apache Airflow — Designing a Daily Pipeline with External DependenciesData Engineeringmedium

Advanced dbt — Diagnosing Three Production IncidentsData Engineeringmedium

Data Quality — Diagnosing Three Trust-Eroding IncidentsData Engineeringmedium

Choosing Streaming or Batch for Two Data ProductsData Engineeringmedium

dbt Three-Layer Architecture for Customer HealthData Engineeringmedium

Star Schema for a Subscription SaaS Data WarehouseData Engineeringmedium

95th percentile trailing value across 1000 orders per rowData Engineeringmedium

Identify sequence gaps: return first and last missing IDData Engineeringmedium

Rank transactions by amount within user partitions, ties broken by timestampData Engineeringmedium

Employee hierarchy with full management chain as arrayData Engineeringmedium

Data skew in partition causing task straggler bottleneckData Engineeringmedium

Longest consecutive daily login streak per userData Engineeringmedium

Broadcast Join vs Shuffle Join in SparkData Engineeringmedium

Implement dbt Column Level Lineage Tracking Snowflake StackData Engineeringmedium

Cloud Warehouse Cost — Diagnosing a $45k Snowflake BillData Engineeringhard

Data Quality — Preventing Three Production IncidentsData Engineeringhard

CDC — Designing a Debezium Pipeline and Handling Schema ChangesData Engineeringhard

Spark Internals — Diagnosing and Fixing a Skewed JoinData Engineeringhard

Company-verified Pro

Real Data Engineering for AI questions reported from interviews at 50+ AI companies, with the golden answer and full scoring. Unlock with Pro →

CDC Log-Based Versus Trigger-Based: Implementation Trade-offsReported at LinkedIneasy
Feature Store — Backfilling a New Feature Without DowntimeReported at Ubermedium
Airflow — Executor Choice and Correct Retry SemanticsReported at Airbnbmedium
Feature Store — When It Earns Its ComplexityReported at Ubermedium
Users with session count growth for three consecutive monthsReported at Airbnbmedium
Product Daily Revenue Rolling 30-Day Percentile Rank CalculationReported at Amazonmedium
Feature drift detection pipeline with automated monitoring and alerting systemReported at Metamedium
User purchase median interval calculation with window functionsReported at Netflixmedium
Seven Day Rolling Average Daily Active Users Including Zero DaysReported at Stripemedium
DBT Model Performance Degradation: Diagnosis and Optimization StrategyReported at Stripemedium
Snowflake Micro-Partitions: Design, Clustering Keys, Performance Trade-offsReported at Snowflakemedium
Ride-level fact table with trip completion metrics and surge multipliersReported at Ubermedium
User lifetime net revenue and distinct active months countReported at Ubermedium
Schema Evolution — Surviving Weekly Proto Changes Across 30 ServicesReported at Confluenthard
Airflow — Cross-DAG Dependencies and Dynamic Fan-OutReported at Airbnbhard
Airflow — Design an Idempotent Backfill DAG with Late-Arriving DataReported at Airbnbhard
Feature Store — Eliminating Online/Offline Skew for Real-Time FraudReported at Uberhard
Delta Lake Time Travel: Querying Historical Table VersionsReported at Databrickshard
Spark Join OOM: Check broadcast threshold and shuffle partition configurationReported at Databrickshard
Streaming Clickstream Lakehouse: Storage, Compaction, Queries, Schema EvolutionReported at Databrickshard

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