Azure Data Engineer Associate
Practice batch and streaming data solutions on Azure, with ingestion, partitioning, security, monitoring and optimization.
120 questions · 9 domains
Understand the scope and access before you start.
11 certifications available · 2 coming soon
Practice batch and streaming data solutions on Azure, with ingestion, partitioning, security, monitoring and optimization.
120 questions · 9 domains
Practice the Databricks Lakehouse Platform, ELT with Spark SQL and Python, incremental processing, production pipelines and governance.
180 questions · 5 domains
Practice advanced Databricks data engineering: ingestion, modeling, Python and SQL pipelines, governance, security and cost tuning.
310 questions · 10 domains · Updated Sep 10, 2026
Practice designing, building, deploying and evaluating generative AI applications on Databricks, including data preparation.
138 questions · 6 domains
Practice developing, testing, documenting and deploying dbt models, plus debugging, environments, governance and pipeline management.
245 questions · 12 domains
Practice designing, building and running data processing systems on Google Cloud, from ingestion and storage to analysis.
74 questions · 5 domains
Practice Snowflake administration: security and RBAC, account management, governance, data sharing, replication and recovery.
198 questions · 5 domains
Practice architecture-level Snowflake decisions across account security, data engineering and performance optimization.
258 questions · 4 domains
Practice advanced Snowflake data engineering: data movement, transformation, performance optimization, storage and security.
178 questions · 5 domains
Practice Snowflake architecture, account security, performance, data loading, transformations and data sharing.
603 questions · 6 domains
Practice Terraform basics, infrastructure as code concepts, the core workflow, state, and reading and writing configuration.
180 questions · 7 domains
Not available to practice yet. Open one to see what it will cover.
Focused Snowflake practice on dynamic tables, streaming and performance.
Practice data science on Snowflake: data preparation, feature engineering, model development and deployment.