Step-by-Step Learning Stages
SQL Data Modeling & Dimensional Architecture
Master dimensional modeling (Kimball Star Schema & Snowflake Schema), primary/foreign key indexing, CTEs, PostgreSQL, and Data Normalization.
Cloud Data Warehousing & Object Storage
Store and query petabyte-scale data using Snowflake, Google BigQuery, Amazon Redshift, AWS S3, and Delta Lake format.
Distributed Processing with Apache Spark
Process massive datasets with PySpark, Spark SQL, Databricks clusters, partition tuning, and distributed join optimization.
Workflow Orchestration & Transformation (Airflow & dbt)
Schedule DAG pipelines using Apache Airflow or Dagster. Modularize warehouse SQL transformations using dbt (data build tool).
Real-Time Event Streaming with Apache Kafka
Ingest sub-second data streams using Apache Kafka, Confluent, Spark Structured Streaming, and real-time dashboards.
Recommended Portfolio Projects
3 real-world projects demonstrating scalable data pipeline architecture.
Automated Financial Market ETL Pipeline
Fetch daily stock/crypto API data using Python, schedule Airflow DAGs, and store structured partitions in PostgreSQL.
E-Commerce Data Warehouse with dbt & Snowflake
Model raw transactional logs into a Kimball star schema using Snowflake, transform data with dbt, and run automated GitHub Actions data tests.
Real-Time Clickstream Streaming Platform
Produce web clickstream events into Apache Kafka, aggregate 1-minute window metrics using Spark Streaming, write to Delta Lake, and plot live Grafana metrics.