Technical Quizzes
Put your knowledge to the test with interactive quizzes covering the skills employers care about most.
Data Engineering Technical Skill Assessments
Validate your knowledge with 250+ production-grade scenario questions across 26 modular assessments with instant technical feedback.
Databricks Quiz — Lakehouse Foundations (Reality Check)
Validate your core understanding of Databricks Lakehouse architecture, Apache Spark integration, Delta Lake ACID transactions, and notebook environments.
Databricks Quiz — Production Data Engineering & Delta Lake Operations
Test your understanding of Spark transformations, Delta Lake schema evolution, automated job scheduling, cluster concurrency, and Time Travel.
Databricks Quiz — Advanced Performance & Optimization
Test your understanding of Delta Lake Z-Ordering, Optimistic Concurrency Control, Broadcast Joins, Medallion ETL, and Structured Streaming exactly-once semantics.
Databricks Quiz — Expert Performance, Debugging & Optimization
Test your expert debugging skills in Databricks: Spark UI profiling, data skew mitigation, Delta cache utilization, memory sizing, and execution plan analysis.
Databricks Quiz — Mastering Governance, Security & Scaling
Test your expertise on Unity Catalog access governance, row/column masking, RocksDB state stores, Change Data Feed, and multi-cloud infrastructure.
Databricks Quiz — ML & AI in Production
Test your knowledge of MLflow model deployment, Adaptive Query Execution (AQE), Feature Stores, deletion vectors, and data skipping.
Databricks Quiz — Architecting for Scale & Best Practices
Test your master-level Databricks architectural expertise: Liquid Clustering, Delta Live Tables (DLT) expectations, system tables, and FinOps optimization.
PySpark Quiz — Basics: Architecture, DataFrames & RDDs
Test your foundational knowledge of PySpark distributed architecture, SparkSession initialization, RDD vs DataFrame trade-offs, and transformations vs actions.
PySpark Quiz — Intermediate: Transformations, Joins & UDFs
Test your understanding of PySpark DataFrame aggregations, conditional column expressions, inner/left joins, User Defined Functions (UDFs), and caching.
PySpark Quiz — Advanced: Window Functions, Shuffles & Execution Plans
Test your understanding of PySpark Window specifications, repartition vs coalesce, Broadcast Hash Joins, and Catalyst physical execution plans.
PySpark Quiz — Expert: Structured Streaming & MLlib Pipelines
Test your knowledge of PySpark Structured Streaming triggers, checkpointing, time-based windows, VectorAssembler, and MLlib regression evaluators.
PySpark Quiz — Expert Level 2: Optimization & Cluster Tuning
Test your expert cluster tuning skills in PySpark: shuffle partition sizing, key salting for data skew, Broadcast joins, and physical plan analysis.
PySpark Quiz — Structured Streaming & Production Pipelines
Test your production streaming skills in PySpark: Kafka ingestion, tumbling event-time windows, withWatermark late-data handling, Delta Lake sinks, and foreachBatch.
PySpark Quiz — MLlib Advanced & Production Pipelines
Test your distributed machine learning skills in PySpark: VectorAssembler feature pipelines, StringIndexer, LogisticRegression, cross-validation, and model persistence.
Snowflake Quiz — Basics & Core SQL
Master Snowflake foundational architecture, virtual warehouses, table hierarchies, external stages, VARIANT semi-structured storage, and RBAC fundamentals.
Snowflake Quiz — Intermediate SQL & Semi-Structured Data
Master Snowflake SQL expressions, Common Table Expressions (CTEs), FLATTEN on JSON arrays, lateral joins, window ranking functions, external stage queries, and MERGE INTO upserts.
Snowflake Quiz — Performance, Clustering & Scaling
Master Snowflake performance optimization, micro-partition architecture, clustering keys, warehouse resizing, 3-tier caching, and Query Profile diagnostics.
Snowflake Quiz — Streams, Tasks & Data Pipelines
Master Snowflake continuous data engineering pipelines: Table Streams, Change Data Capture (CDC), Task scheduling with cron, DAG dependencies with AFTER, and automated Snowpipe ingestion.
Snowflake Quiz — Advanced SQL & Semi-Structured Analytics
Master advanced Snowflake analytical SQL: lateral joins with FLATTEN, 7-day moving averages, PIVOT/UNPIVOT, JSON MERGE into staging, complex VARIANT path extractions, cumulative sums, deduplication via ROW_NUMBER, ARRAY_CAT, window percentage contributions, and semi-joins.
Snowflake Quiz — Security, Roles & Governance
Master Snowflake enterprise governance: Role-Based Access Control (RBAC), Custom Roles, System-Defined Roles, Dynamic Data Masking policies, Row Access Policies, Secure Data Sharing, and privilege auditing.
Snowflake Quiz — Advanced Administration & Optimization
Master enterprise Snowflake administration: Zero-Copy Cloning, Multi-Cluster Warehouses, Cross-Region Business Continuity & Failover, ACCOUNT_USAGE credit monitoring, and FinOps compute cost optimization.
Apache Airflow Quiz — Beginner: Core Architecture & DAG Fundamentals
Test and solidify your foundational knowledge of Apache Airflow architecture, DAG components, Schedulers, Webservers, and task dependencies.
Apache Airflow Quiz — Intermediate: DAG Development & Operators
Test your understanding of Airflow DAG development, default_args inheritance, Python and Bash operators, Jinja templating, and connection management.
Apache Airflow Quiz — Advanced: XComs, Branching & TaskFlow API
Test your advanced Apache Airflow expertise covering XCom data passing, BranchPythonOperator conditional logic, TaskFlow decorators, and trigger rules.
Apache Airflow Quiz — Expert: Metadata, Logging & Monitoring
Test your expert knowledge on Airflow metadata database architecture, remote logging to S3/GCS, secrets backends, SLAs, and CI/CD validation.
Apache Airflow Quiz — Master: Data-Aware Scheduling & Production Architecture
Test your master-level Apache Airflow expertise on Data-Aware Scheduling (Datasets), cross-DAG dependencies, custom operators, and enterprise governance.
🛡️ Assessment Design Principles
- Production-Grounded Scenarios: Questions are derived from real cluster bottlenecks, skew issues, and production failures.
- Trade-Off Reasoning: Focuses on architectural trade-offs (cost vs latency, storage vs compute decoupling) rather than trivial syntax memorization.
- Immediate Distractor Analysis: Every option explains why it is correct or why it fails under production constraints.