Data Engineering & Real-Time Lakehouse Architect Career Guide
Design petabyte-scale batch & streaming data pipelines, medallion lakehouse architecture, and real-time Kafka transformations with Apache Spark and dbt.
Interactive Sprint Milestones & DevScore
Every milestone includes an interactive proof hook: complete the technical knowledge check or submit your GitHub deliverable to earn +30 DevScore XP.
Columnar Storage, Partitioning & Star Schema
In-Depth Curriculum & Video Masterclasses
Curated step-by-step guides with zero paid subscriptions. Complete the hands-on project before advancing.
Data Warehousing & SQL Query Optimization
Columnar storage formats (Parquet, ORC), query clustering, partitioning, and complex analytical SQL.
Ingest and model raw ride data in BigQuery/PostgreSQL with partitioned tables and optimized indexing.
Distributed Batch Processing with Apache Spark
PySpark DataFrames, Spark SQL, Catalyst Optimizer, DAG physical plans, and memory shuffles.
Process raw web server access logs with PySpark, partition by date and status, and output compressed Parquet.
Real-Time Streaming with Kafka & Spark Streaming
Event stream ingestion, windowed aggregations, watermarking, and exactly-once processing semantics.
Detect anomalous credit card transactions in sub-second windows using Kafka topics and Spark Structured Streaming.
Modern Medallion Lakehouse & Airflow Orchestration
Bronze/Silver/Gold Lakehouse architecture with Delta Lake/Iceberg, automated dbt ELT, and Airflow DAGs.
Build an end-to-end automated pipeline orchestrated with Airflow, transforming raw data into business-ready Gold marts using dbt and Delta Lake.
Live Industry Roles Requiring Data Engineering & Real-Time Lakehouse Architect Skills
Industry hiring requirements matching these curriculum milestones. Master these nodes to pass screening.