“The Microsoft Fabric implementation program gave our data engineering team a structured path from legacy pipelines to a modern lakehouse architecture.”
Enterprise Program Brief
Azure Data Engineering with Databricks
A hands-on data engineering program covering end-to-end pipeline development on Azure, from raw ingestion through transformation to serving. Participants work with Apache Spark, Delta Lake, and Azure Data Factory under real pipeline design constraints, not simplified examples.
VNode ITeSIntermediate
Download Program Brief (PDF)Program Snapshot
Engagement scoped to cohort
Duration5 days
FormatVirtual or On-site
LevelIntermediate
- MCT-led delivery
- Private cohort / virtual ILT
- Typical response: 1 business day
Scoping call typically scheduled within one business day
VNode ITeS delivers Azure Data Engineering with Databricks as an MCT-led VNode ITeS program for Data engineers and architects building or modernizing data platforms on Azure. Typical duration is 5 days (Virtual or On-site). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.
Audience Profile
Built for these roles
Data engineers and architects building or modernizing data platforms on Azure
- Tailored Team Delivery
- Implementation-Focused
Overview
Executive overview
Build scalable data pipelines using Azure Databricks, Delta Lake, and Apache Spark. Covers medallion architecture and ADF integration.
Prerequisites
- SQL proficiency
- Basic Python or Scala
- Familiarity with cloud storage concepts
Program Outcomes
Capabilities your teams will gain
- Design and build Bronze-Silver-Gold medallion pipelines
- Use ADF orchestration with Databricks compute
- Implement data quality checks and lineage tracking
- Optimize Spark jobs for cost and performance at scale
Enterprise Delivery
Private cohort delivery
VNode-designed, vendor-aligned instructor-led program. Scope role mix, delivery format, and rollout goals for your cohort.
Curriculum
Curriculum roadmap
- Delta Lake and medallion architecture design
- Apache Spark optimization and performance tuning
- Azure Data Factory orchestration with Databricks
- Data quality and Unity Catalog governance
1Module 1
Delta Lake and Medallion Architecture
+
Module 1
Delta Lake and Medallion Architecture
Design and implement Bronze-Silver-Gold pipeline patterns using Delta Lake, schema management, and incremental processing for scalable data platforms.
- implement Bronze-Silver-Gold pipeline patterns using Delta Lake
- schema management
- and incremental processing for scalable data platforms
2Module 2
Apache Spark Optimization
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Module 2
Apache Spark Optimization
Write and tune Spark jobs for cost-efficient processing at enterprise scale, covering partitioning, caching, and cluster configuration.
- tune Spark jobs for cost-efficient processing at enterprise scale
- covering partitioning
- and cluster configuration
3Module 3
Azure Data Factory Orchestration
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Module 3
Azure Data Factory Orchestration
Build ADF-triggered pipeline workflows that invoke Databricks compute, monitor job runs, and handle failures with retry and alerting logic.
- Build ADF-triggered pipeline workflows that invoke Databricks compute
- monitor job runs
- and handle failures with retry
- alerting logic
4Module 4
Data Quality and Unity Catalog
+
Module 4
Data Quality and Unity Catalog
Implement data quality checks, lineage tracking, and catalog-level governance using Databricks Unity Catalog for enterprise data reliability.
- Implement data quality checks
- lineage tracking
- and catalog-level governance using Databricks Unity Catalog for enterprise data reliability
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
- Implementation-focused labs
- Private cohort delivery
- Intermediate practitioner depth
- Business outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Prepares data teams to design and deliver scalable, production-grade pipelines using the Azure Databricks ecosystem, reducing rework during platform rollout.
- Align dataset and schema to team's existing sources
- Include Unity Catalog configuration and access control
- Add structured streaming module (Event Hubs or Kafka)
Resources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios
