Data Engineering
Data engineering drills cover the full production stack — ETL/ELT foundations, cloud warehousing (Snowflake, BigQuery, Redshift), lakehouse formats (Delta, Iceberg), streaming (Kafka, Spark, Flink), orchestration (Airflow, dbt), and production concerns like cost, observability, and GDPR. From L1 screens at TCS and mu_sigma to staff-level architecture rounds at Databricks, Uber, and Stripe.
What this skill is about
Data engineering drills cover the full production stack — ETL/ELT foundations, cloud warehousing (Snowflake, BigQuery, Redshift), lakehouse formats (Delta, Iceberg), streaming (Kafka, Spark, Flink), orchestration (Airflow, dbt), and production concerns like cost, observability, and GDPR. From L1 screens at TCS and mu_sigma to staff-level architecture rounds at Databricks, Uber, and Stripe.
Topics we drill
- Data Engineering Foundations
- Data Warehousing
- Lakehouse & Open Formats
- Streaming Pipelines
- Apache Spark
- Orchestration & Transformation
- Data Quality & Contracts
- Data Modeling
- Production Data Engineering
Why this matters at interviews
Real interviewers don’t just check if you know the syntax — they probe whether you’ve used the concept under production pressure. Our drills mirror that. Adaptive difficulty, named anti-patterns called out as you go, and a senior-staff voice that teaches the production vocabulary rather than dumbing it down.