Databricks Data Engineer Associate - Study Plan¶

5-Week Study Schedule¶

Week 1: Lakehouse Platform and Spark SQL Basics (Domains 1-2)¶

Day 1-2: Lakehouse Architecture¶

• Understand Lakehouse vs data warehouse vs data lake
• Learn the Databricks platform architecture (control plane vs data plane)
• Explore the Databricks workspace interface
• Review Notes: notes/01-lakehouse-platform.md
• Read: Lakehouse Architecture

Day 3-4: Compute Resources and Workspace¶

• Understand cluster types: all-purpose, job, SQL warehouse, serverless
• Learn autoscaling, spot instances, and cluster pools
• Practice notebook magic commands (%sql, %python, %run)
• Explore dbutils utilities (fs, secrets, widgets)
• Read: Compute Overview

Day 5-6: Spark SQL Fundamentals¶

• Review SELECT, JOIN, GROUP BY, and WHERE clauses
• Practice window functions (ROW_NUMBER, RANK, LAG, LEAD)
• Learn Common Table Expressions (CTEs)
• Understand temporary views vs global temporary views
• Review Notes: notes/02-elt-spark-sql.md
• Read: SQL Reference

Day 7: Week 1 Review¶

• Review all notes from this week
• Quiz yourself on Lakehouse architecture benefits
• Practice identifying correct compute type for given scenarios
• Create flashcards for key SQL functions

Week 2: ELT Deep Dive and Delta Lake (Domain 2)¶

Day 8-9: Reading and Writing Data¶

• Practice reading CSV, JSON, and Parquet files
• Learn COPY INTO for batch data loading
• Understand save modes (append, overwrite, errorIfExists, ignore)
• Practice CTAS and CREATE OR REPLACE TABLE statements
• Read: Data Sources

Day 10-11: MERGE INTO and Complex Transformations¶

• Master MERGE INTO for upsert operations
• Practice complex data types: arrays, structs, maps
• Learn higher-order functions: transform, filter, exists
• Practice explode, posexplode, and collect_set/collect_list
• Read: MERGE INTO

Day 12-13: Delta Lake Fundamentals¶

• Understand ACID transactions on Delta Lake
• Learn time travel (VERSION AS OF, TIMESTAMP AS OF, RESTORE)
• Practice OPTIMIZE, VACUUM, and Z-ordering commands
• Understand schema enforcement and schema evolution
• Read: Delta Lake Overview

Day 14: Week 2 Review¶

• Review the multi-hop (medallion) architecture pattern
• Practice writing MERGE INTO statements from scratch
• Review Delta Lake transaction log concepts
• Take notes on areas of confusion

Week 3: Incremental Processing (Domain 3)¶

Day 15-16: Structured Streaming Basics¶

• Understand readStream vs read, writeStream vs write
• Learn trigger modes: default, processingTime, availableNow
• Understand output modes: append, complete, update
• Learn checkpointing and exactly-once guarantees
• Review Notes: notes/03-incremental-processing.md
• Read: Structured Streaming

Day 17-18: Auto Loader¶

• Learn the cloudFiles format and configuration options
• Understand file notification vs directory listing modes
• Practice schema inference and schema evolution settings
• Know when to use Auto Loader vs COPY INTO
• Read: Auto Loader

Day 19-20: Streaming Advanced Topics¶

• Understand watermarking for late-arriving data
• Learn stream-static joins
• Practice streaming with Delta Lake as source and sink
• Understand deduplication in streaming contexts
• Read: Watermarks

Day 21: Week 3 Review¶

• Compare Auto Loader vs COPY INTO in a reference table
• Review all trigger modes and output modes
• Practice writing streaming pipelines from scratch
• Quiz yourself on checkpointing requirements

Week 4: Production Pipelines and Governance (Domains 4-5)¶

Day 22-23: Delta Live Tables¶

• Learn DLT table and view decorators (Python) and SQL syntax
• Master all three expectation types (expect, expect_or_drop, expect_or_fail)
• Understand pipeline modes: triggered vs continuous
• Learn about the DLT event log for monitoring
• Review Notes: notes/04-production-pipelines.md
• Read: Delta Live Tables

Day 24-25: Databricks Jobs and Workflows¶

• Create multi-task jobs with dependencies
• Learn task types: notebook, Python, SQL, DLT, dbt
• Understand scheduling (cron), notifications, and retry policies
• Practice passing values between tasks with dbutils.jobs.taskValues
• Read: Databricks Jobs

Day 26-27: Unity Catalog and Governance¶

• Master the three-level namespace: catalog.schema.table
• Practice GRANT and REVOKE statements
• Understand managed vs external tables
• Learn dynamic views for row and column security
• Review Notes: notes/05-data-governance.md
• Read: Unity Catalog

Day 28: Week 4 Review¶

• Review DLT expectations and their behaviors
• Practice writing GRANT statements from scratch
• Review data lineage and information schema concepts
• Compare managed vs external tables

Week 5: Exam Preparation and Practice¶

Day 29-30: Comprehensive Review¶

• Re-read all five notes files
• Review the fact sheet for quick reference
• Focus on the two largest domains: ELT (29%) and Lakehouse Platform (24%)
• Create a one-page summary of key concepts

Day 31-32: Practice Scenarios¶

• Work through scenarios.md exam-style questions
• Take any available practice exams
• Review incorrect answers and identify weak areas
• Re-read documentation for topics you struggle with

Day 33-34: Final Preparation¶

• Review key differentiators (Auto Loader vs COPY INTO, managed vs external)
• Practice time management: 2 minutes per question
• Review Delta Lake commands one final time
• Skim the strategy guide for exam-day tactics

Day 35: Exam Day¶

• Light review of fact sheet only - no heavy studying
• Ensure stable internet and quiet environment
• Have valid ID ready for proctoring
• Take the exam with confidence

Study Tips¶

Time Allocation by Domain Weight¶

Recommended Daily Schedule¶

• 30 min reading documentation or notes
• 30 min hands-on practice on Databricks Community Edition
• 15 min reviewing flashcards or key concepts
• Total: ~1.25 hours/day

Key Resources¶

• Databricks Community Edition - Free practice environment
• Databricks Academy - Free learning paths
• Exam Guide - Official exam page