Client Readiness — Databricks Data Engineering
Build a client-ready technical profile with sharpened SQL, PySpark, and Spark internals skills paired with interview preparation.
Your Skill Path
15 modules · Masterclasses, hands-on scenarios & timed mock tests
Advanced SQL — Window Functions, CTEs & Query Performance Tuning
Write and Optimize Complex SQL Queries for Analytical Reporting
Python for Data Engineering — PySpark Essentials & Data Manipulation
Apply PySpark Transformations, DataFrame Operations and UDFs on Real Datasets
Spark Core — Execution Model, DAG, Shuffles, AQE & Optimization Internals
Analyze a Spark Execution Plan, Identify Bottlenecks and Apply Targeted Optimizations
Cloud Fundamentals — Azure / AWS / GCP for Databricks Data Engineering
Configure Cloud Storage Access, Networking and Permissions for a Databricks Deployment
Databricks Architecture — Clusters, Workspace, Runtime & Cluster Configuration
Configure and Right-Size a Databricks Cluster for a Production Workload Scenario
Databricks Workflows & Unity Catalog — Job Orchestration & Data Governance
Build a Multi-Task Workflow with Unity Catalog Integration and Failure Handling
Scenario Walkthroughs — Explain Architecture Decisions, Trade-offs and Design Choices
Optimization Reasoning — Articulate Spark and Pipeline Optimization Decisions Under Pressure
End-to-End Architecture Articulation — Present a Complete Data Engineering Solution to a Panel
Ready to get started?
Get a walkthrough of this skill path and see how Enqurious can accelerate your growth on Databricks.
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