Databricks Data Engineer Professional – Recommended Study Order

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Got it — I’ll arrange these topics into a logical learning order so you build knowledge step-by-step, starting from fundamentals and moving toward advanced Databricks optimization topics.

Databricks Data Engineer Professional – Recommended Study Order

1. Core Foundations

  1. Cloud Infrastructure & Security (15%)
    • Understand AWS/Azure/GCP basics for Databricks, networking, IAM, and cluster security.
  2. Governance (Unity Catalog, ACLs) (10%)
    • Learn data governance, permissions, and Unity Catalog features.
  3. Cluster Basics
    • Types of Clusters & Optimizations
    • Cluster Policy
    • Cluster Config – Best Practices
    • What are Disk-operated Clusters / Memory Management
    • Memory Issues

2. Spark & Databricks Fundamentals

  1. Spark Core & Tuning (25%)
    • Spark architecture, RDDs, DataFrames, lazy execution, caching, and performance tuning.
  2. Photon Engine
    • Learn Databricks’ optimized query engine and when it’s beneficial.

3. Data Storage & Processing

  1. Delta Lake & Delta Live Tables (20%)
    • ACID transactions, schema evolution, time travel, Z-ordering, Liquid Clustering.
  2. Hash Functions
    • Understand usage in partitioning, joins, and deduplication.

4. Data Pipelines & Streaming

  1. Lakeflow Declarative Pipelines
    • Declarative ETL orchestration, Auto Loader, dependency handling.
  2. Streaming (Structured Streaming, Kafka) (15%)
    • Batch vs streaming, triggers, watermarks, Kafka integration, processing guarantees.
  3. Kafka
  • Specific producer-consumer concepts and integration with Spark.

5. Data Modeling & Optimization

  1. Modelling
  • Star/Snowflake schema, medallion architecture.
  1. Cost & Performance Optimization (10%)
  • Query tuning, caching, partitioning, data skipping, autoscaling.

6. Machine Learning & AI

  1. Machine Learning / MLflow (5%)
  • Experiment tracking, feature store, model registry.
  1. ML
  • Model training, deployment, and ML runtime environment.
  1. Generative AI & Advanced Tuning (Optional but useful)
  • Databricks AI functions, LLM integration, fine-tuning models.

Final Step – Advanced Topics & Review

  1. Databricks Advanced Tuning
  2. Z-order (covered under Delta Lake)
  3. Liquid Clustering (covered under Delta Lake)
  4. End-to-End Exam Practice
  • Use official Databricks sample questions & hands-on labs.

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