Azure Data Engineer (DP-203) Certification Training

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Assure Success

About the course

Why take Azure Data Engineer (DP-203) Certification Training?

Azure Data Engineer (DP-203) validated the skills to integrate, transform and consolidate data from many sources into analytics-ready stores. Microsoft retired the DP-203 exam and the Azure Data Engineer Associate certification on 31 March 2025, so it can no longer be taken. Microsoft's current data engineering certification path centres on Microsoft Fabric (Fabric Data Engineer Associate, exam DP-700); please confirm the current status and outline on Microsoft Learn before booking.

The technical content of DP-203 is still the backbone of Azure data engineering jobs, which is why this course is still valuable. Over 45 live hours you design data lake and warehouse storage, build batch pipelines with Azure Data Factory and Synapse, transform data with Spark in Databricks and Synapse, process streams with Event Hubs and Stream Analytics, and secure, monitor and optimise the platform. A bridge module introduces how the same ideas appear in Microsoft Fabric.

There is no exam inside the course. Delivery is live, instructor-led and online.

Who should attend

● Data engineers and ETL developers moving to Azure
● Database and BI developers who want to build modern pipelines
● Data analysts who want to move into engineering
● Software engineers working with large or streaming data
● Cloud engineers supporting data platforms

Prerequisites

● Solid SQL skills
● Working knowledge of Python (or Scala) for data processing
● Basic understanding of data warehousing concepts
● Basic Azure knowledge (AZ-900 or DP-900 level) is helpful

What this certification does for you

Complete data engineering stack

Storage, processing, streaming and governance in one program.

Transparent about certification

You learn the retirement status and the current Fabric-based path.

Lakehouse project

Finish with an end-to-end pipeline you can demonstrate.

Transferable skills

Spark, SQL and medallion design apply across platforms.

Curriculum

9 modules, step by step

MODULE 1

Azure Data Platform Overview

Map the services to the data lifecycle.

› Data engineering responsibilities
› Azure data services landscape
› Lakehouse and warehouse concepts
› Lab environment setup

MODULE 2

Data Lake Storage Design

Design the storage layer.

› ADLS Gen2 hierarchy and ACLs
› Folder structure and partitioning
› Parquet, Delta and file formats
› Data retention and archiving

MODULE 3

Synapse Analytics and SQL Pools

Serve analytical queries.

› Serverless vs dedicated SQL pools
› Distribution types and indexes
› External tables and PolyBase concepts
› Materialised views and result caching

MODULE 4

Data Factory and Synapse Pipelines

Orchestrate batch ingestion.

› Linked services, datasets and activities
› Mapping data flows
› Triggers, parameters and incremental loads
› Error handling and retries

MODULE 5

Spark Processing with Databricks and Synapse

Transform data at scale.

› Spark architecture and DataFrames
› Delta Lake basics
› Notebooks and jobs
› Performance: partitions, skew and caching

MODULE 6

Dimensional Modelling and Medallion Layers

Shape data for analytics.

› Star schemas and SCD types
› Bronze/silver/gold layering
› Data quality checks
› Serving to Power BI

MODULE 7

Streaming Data

Process real-time events.

› Event Hubs and Kafka endpoint
› Stream Analytics queries and windowing
› Spark Structured Streaming overview
› Late data and exactly-once ideas

MODULE 8

Security, Governance and Monitoring

Operate responsibly.

› Managed identities, Key Vault and RBAC
› Encryption, masking and network isolation
› Microsoft Purview concepts
› Azure Monitor and pipeline alerts

MODULE 9

Optimisation, Fabric Bridge and Capstone

Tune the platform and look ahead.

› Cost and performance tuning
› Introduction to Microsoft Fabric: OneLake, Lakehouse, pipelines
› Mapping DP-203 skills to the current Fabric path
› Capstone pipeline presentation

Certification exam

DP-203 was retired on 31 March 2025. Microsoft's current data engineering certification is built around Microsoft Fabric (Fabric Data Engineer Associate, exam DP-700)

Awarded by	Microsoft
Format	Proctored exam; confirm the current outline on Microsoft Learn before booking
Questions	See the current figure on the official site
Duration	See the current figure on the official site
Passing score	See the current figure on the official site
Exam fee	See the current figure on the official site
Where	Pearson VUE test centre or online proctored
Validity	See the current figure on the official site

Your path to certification

1
Enrol in a live batch and attend the 45 hours of instructor-led sessions
2
Complete the pipeline labs and the capstone lakehouse project
3
Receive an Assure Success course-completion certificate after meeting attendance and project requirements
4
Optional: review Microsoft's current Fabric data engineering certification on Microsoft Learn and book that exam yourself with Pearson VUE

Skills you will gain

Data storage design

Design data lakes, partitioning, file formats and serving layers on ADLS Gen2 and Synapse.

Batch pipelines

Build and schedule pipelines with Azure Data Factory and Synapse pipelines.

Spark transformations

Transform and clean data using Spark in Azure Databricks and Synapse.

SQL-based analytics

Model data in dedicated and serverless SQL pools and optimise queries.

Streaming

Ingest and process real-time data with Event Hubs and Stream Analytics.

Data modelling

Build star schemas, slowly changing dimensions and medallion (bronze/silver/gold) layers.

What you get