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Azure Data Engineering Corporate Training Program for Employees
Give your data engineering team the skills to design, build, and operate reliable, scalable data pipelines on Azure, through instructor-led training customized to your environment and delivered onsite or online.
(Virtual / On-site / Off-site)
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Equip Your Data Teams to Build and Run Data Pipelines on Azure
Azure data engineering is the practice of designing, building, and operating data pipelines, storage, and processing systems on Microsoft Azure, using services such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure Data Lake Storage to turn raw data into analytics-ready datasets. As organizations move their data platforms to the cloud, the teams that can build reliable, scalable, and secure pipelines become business-critical, and this training builds exactly that capability.
As enterprises consolidate their data on Azure and expect trustworthy, real-time analytics, this program helps your teams ingest, transform, and serve data with confidence. Empower your people with expert-led on-site, off-site, and virtual sessions delivered by Edstellar, a premier corporate training provider serving organizations worldwide. Built around your goals, the program turns Azure data engineering skills into lasting capabilities that lift performance across data, analytics, and platform engineering teams.
The result is faster, more reliable data delivery, lower pipeline maintenance costs, stronger data governance and security, and a team that can support analytics and AI workloads without constant rework. Sessions are instructor-led, customized to your Azure data stack, and available worldwide in multiple languages, so the training maps directly to the platforms your organization runs today.
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- Design and build batch and streaming data pipelines using Azure Data Factory and Synapse pipelines.
- Ingest, transform, and load data at scale with Azure Databricks, Apache Spark, and mapping data flows.
- Model and manage analytics storage with Azure Data Lake Storage and Azure Synapse Analytics.
- Implement data security, governance, and access control across the Azure data platform.
- Monitor, optimize, and troubleshoot pipelines for performance, reliability, and cost.
- Deliver clean, well-structured, analytics-ready data that supports reporting and machine learning workloads.
- Module 1
- Core Azure data services: Data Factory, Synapse, Databricks, and Data Lake Storage
- Relational, non-relational, and analytical data stores on Azure
- The data engineering workflow: ingest, store, process, and serve
- Provisioning and securing Azure data resources
- Module 2
- Azure Data Lake Storage Gen2 and the medallion (bronze, silver, gold) architecture
- Designing partitioning, file formats, and folder structures for scale
- Relational modeling in Azure SQL and dedicated SQL pools
- Choosing the right store for batch and analytical workloads
- Module 3
- Building pipelines with Azure Data Factory and Synapse pipelines
- Connecting to on-premises, cloud, and SaaS data sources
- Scheduling, triggers, parameters, and pipeline orchestration
- Incremental loads and change data capture
- Module 4
- Large-scale transformation with Azure Databricks and Apache Spark
- Mapping data flows and code-free transformation
- Batch and streaming processing patterns
- Working with Delta Lake for reliable, ACID-compliant data
- Module 5
- Serving data with Azure Synapse Analytics SQL and Spark pools
- Real-time analytics with Azure Stream Analytics and Event Hubs
- Integrating with Power BI for downstream reporting
- Optimizing queries and data delivery for consumers
- Module 6
- Securing data with role-based access, managed identities, and encryption
- Data governance and lineage with Microsoft Purview
- Monitoring pipelines and managing operational reliability
- Performance tuning and cost optimization across the data platform
- Data Engineers
- Data Architects
- Database Administrators
- BI Developers
- Data Scientists
- Data Analysts
- ETL Developers
- Cloud Data Engineers
- IT Administrators
- Data Warehousing Managers
- Cloud Engineers
- Business Intelligence Analysts
Participants should be comfortable writing SQL and have basic programming experience, ideally in Python or Scala, along with a general understanding of databases and core cloud concepts. Familiarity with the Azure portal is helpful but not required, the program is designed to take data, analytics, and BI teams from working knowledge to confident, hands-on Azure data engineering.
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64 hours of group training (includes VILT/In-person On-site)
Tailored for SMBs
160 hours of group training (includes VILT/In-person On-site)
Ideal for growing SMBs
Tailor-Made Trainee Licenses with Our Exclusive Training Packages!
400 hours of group training (includes VILT/In-person On-site)
Designed for large corporations
Tailor-Made Trainee Licenses with Our Exclusive Training Packages!
Unlimited duration
Designed for large corporations
Experienced Trainers
Our trainers are drawn from a vetted global network and bring years of industry expertise, keeping every session practical and impactful.
Proven Quality
With a strong global track record, Edstellar is known for quality and engaging delivery.
Industry-Relevant Curriculum
Our programs are built by experts to match the demands of today's industry.
Fully Customizable
Every program can be tailored to your organization's goals.
Comprehensive Support
We provide pre- and post-session support for a complete learning experience.
Global Multi-Location & Multilingual Training Delivery
We deliver in multiple languages to support diverse global teams.
Hear from Organizations We've Trained
Recognition That Motivates Your Team
Frequently Asked Questions
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