Staff-Level Systems, Lakehouses & AI
11 industrial-grade curriculum tracks covering Python, Pandas, Enterprise SQL, Distributed PySpark, Cloud Data Lakes (AWS, Azure, GCP), Databricks, Snowflake, Airflow, and Power BI DAX. Every track features end-to-end performance tuning and production error forensics.
Specialized Tracks
Deep Lessons
Pipeline Topologies
Prod Failure Modes
Interactive Cloud Data Pipeline Studio
Interactive drag-and-drop pipeline canvases across Azure Data Factory, AWS Serverless Lakehouse, Databricks Delta Live Tables, Apache Airflow, GCP Dataflow, and Snowflake Streaming with live simulation.
Production Error & Troubleshooting Encyclopedia
Real industry stack traces, root causes, log locations (Spark UI, CloudWatch, Databricks, Snowflake query history), and instant copyable fixes for Exit 137 OOMs, Remote Disk Spills, Deadlocks, and S3 throttles.
Data Engineering Performance Optimization Bible
Deep dive into Spark Adaptive Query Execution (AQE), Broadcast vs Sort-Merge joins, Delta Liquid Clustering, Snowflake micro-partition pruning, SARGable SQL, and Power BI VertiPaq cardinality slashing.
Distributed PySpark & Lakehouse Architecture
Catalyst optimizer, Tungsten, memory pools, AQE, broadcast/skew joins with salting, windowing, watermarking, and Structured Streaming.
Enterprise SQL & Query Optimization
Logical execution order, window framing, recursive CTEs, SCD2 merges, B-Tree indexes, and execution plan optimization.
Python for Production Data Engineering
Memory references, streaming generators, multiprocessing vs asyncio, Pydantic v2 validation, decorators, and pytest suites.
Pandas for Production Data Pipelines
BlockManager memory tuning, chunked file processing, vectorized transformations, partitioned Parquet I/O, and Apache Arrow.
AWS Data Engineering & Bedrock AI
S3 lakehouse prefix scaling, AWS Glue Catalogs, Athena partition projection, EMR, Redshift dist/sort keys, and Bedrock GenAI.
Azure Data Engineering & Synapse / OpenAI
ADLS Gen2 hierarchy, Azure Data Factory ADF pipelines, Synapse Analytics SQL pools, Event Hubs, and Azure OpenAI enrichment.
GCP Data Engineering & BigQuery / Vertex AI
Google Cloud Storage, BigQuery slots / clustering / partitioning, Dataflow Apache Beam, Cloud Composer, and Vertex AI.
Databricks, Delta Lake & Unity Catalog
Medallion architecture, Delta Lake transaction logs, Z-ordering, Liquid Clustering, Unity Catalog, Photon, and Mosaic AI.
Snowflake Cloud Data Warehouse & Cortex AI
Multi-cluster compute, micro-partitions, Snowpipe auto-ingest, Streams & Tasks for CDC, Time Travel, and Cortex AI.
Apache Airflow & Pipeline Orchestration
DAG authoring, Taskflow API, Sensors, dynamic task mapping, pools, SLA misses, Kubernetes executor, and GenAI task orchestration.
Power BI, DAX & Semantic Modeling for DE
Kimball star schema, DirectQuery vs Import vs DirectLake in Fabric, DAX evaluation context, incremental refresh, and DAX Studio.