Sophia tests ETL pipeline design, Spark optimization, SQL query tuning, Kafka architecture, and cloud data services.
Data engineering roles test your capacity to model data, design reliable ETL pipelines, utilize distributed frameworks like Spark, manage messaging queues, and orchestrate complex tasks with Airflow.
ETL design: ingestion, transformation, loading, error handling, and partitioning
Apache Spark architecture, RDDs vs DataFrames, query optimization
Kafka consumer groups, offset management, and fault tolerance patterns
SQL optimization: window functions, CTEs, query plans, and indexing strategies
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Sophia covers AWS (Glue, Redshift, S3, EMR), GCP (BigQuery, Dataflow, Pub/Sub), and Azure (Synapse, Data Factory) data services. Specify your preferred cloud in the setup.
Data engineering interviews focus heavily on distributed computing, SQL at scale, pipeline reliability, and big data frameworks. Coding questions are more SQL/Python-heavy rather than pure DSA.