Can the program be customized?

Yes. Implement data engineering solutions using Azure Databricks supports customization around lab depth, demo context, certification focus, and team-specific scenarios.

Yes. This program includes instructor-led labs and practical exercises aligned to real implementation patterns.

How does this align with official certification or curriculum?

This program is aligned to the official Microsoft Learn curriculum and learning path referenced for this track.

How are prerequisites assessed?

We review prerequisite readiness during scoping and can recommend preparatory modules or a skills checkpoint before cohort start.

What happens after the program?

Private cohorts receive a handover summary, recommended next learning paths, and optional follow-on advisory for rollout or certification readiness.

Microsoft Official Curriculum

Implement data engineering solutions using Azure Databricks

Master end-to-end data engineering with Azure Databricks and Unity Catalog. This course moves from foundational setup to production deployment, covering environment configuration and enterprise-grade governance. Learn to build robust ingestion pipelines, implement security with Unity Catalog, and deploy optimized workloads. By the end, you will have the practical skills to implement, secure, and maintain scalable lakehouse solutions that meet rigorous enterprise requirements.

Role-Based Certification PrepTrack: DP-750T00Official Source: Microsoft LearnMicrosoftIntermediate

Plan Private Delivery Consult a Solutions Architect

Download Program Brief (PDF)

Program Snapshot

Engagement scoped to cohort

Duration4 days

FormatVirtual, On-site, or Hybrid

LevelIntermediate

Course CodeDP-750T00

Certification TrackDP-750T00

SubjectData

MCT-led delivery
Private cohort / virtual ILT
Typical response: 1 business day

Scoping call typically scheduled within one business day

VNode ITeS delivers Implement data engineering solutions using Azure Databricks as an MCT-led Microsoft program for Data Engineer. Typical duration is 4 days (Virtual, On-site, or Hybrid). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Certification prep maps to DP-750 without turning the week into a dump of Learn modules. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.

Audience Profile

Built for these roles

The target audience is data engineers who have fundamental knowledge of data analytics concepts, a basic understanding of cloud storage, and familiarity with data organization principles. They should be comfortable working with SQL and have experience using Python, including notebooks, for data engineering tasks. Learners are expected to have a good understanding of Azure Databricks workspaces and Unity Catalog, along with familiarity with data access patterns and core data engineering and data warehouse concepts. In addition, they should have foundational knowledge of Azure security, including Microsoft Entra ID, and be familiar with Git version control fundamentals.

Data Engineer
Data
Certification Readiness
Tailored Team Delivery

Overview

Executive overview

Prerequisites

Relevant foundational experience in the target technology area.
Comfort with hands-on labs in a cloud or GPU-accelerated environment.

Program Outcomes

Capabilities your teams will gain

Strengthen capability in data engineer scenarios
Strengthen capability in azure scenarios

Enterprise Delivery

Official learning & delivery options

Review the vendor learning resource, then book a consultation or request a private cohort for your team.

View Official Learning Book a Consultation Request Private Cohort Open in learning platform Program brief (PDF)

Curriculum

Curriculum roadmap

Data Engineer
Azure

Module 1

Set up and configure an Azure Databricks environment

Build a solid foundation in Azure Databricks by understanding its architecture, integrations, compute options, and data organization capabilities. Learn how Azure Databricks provides a unified platform for data engineering, analytics, and AI workloads in the cloud.

Explore Azure Databricks
Understand Azure Databricks architecture
Understand Azure Databricks Integrations
Select and Configure Compute in Azure Databricks
Create and organize objects in Unity Catalog

Module 2

Secure and govern Unity Catalog objects in Azure Databricks

Learn to implement comprehensive security and governance for your data assets in Azure Databricks using Unity Catalog. Master access control strategies, fine-grained permissions, credential management, and governance practices to build a secure and compliant data platform.

Secure Unity Catalog objects
Govern Unity Catalog objects

Module 3

Prepare and process data with Azure Databricks

Master the essential skills to build robust, scalable data engineering solutions with Azure Databricks and Unity Catalog. Learn to design effective data models, ingest data from diverse sources, transform raw data into analytics-ready formats, and ensure data quality across your lakehouse architecture.

Design and implement data modeling with Azure Databricks
Ingest data into Unity Catalog
Cleanse, transform, and load data into Unity Catalog
Implement and manage data quality constraints with Azure Databricks

Module 4

Deploy and maintain data pipelines and workloads with Azure Databricks

Master the complete lifecycle of building, deploying, and maintaining production-ready data pipelines in Azure Databricks—from design and orchestration to monitoring and optimization.

Design and implement data pipelines with Azure Databricks
Implement Lakeflow Jobs with Azure Databricks
Implement development lifecycle processes in Azure Databricks
Monitor, troubleshoot and optimize workloads in Azure Databricks

Delivery Models

Delivery models

Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend

Engagement Fit

Engagement fit

Certification readiness
Implementation-focused labs
Private cohort delivery
Intermediate practitioner depth

Enterprise Customization

Enterprise customization

Tailor this program to your organization's priorities: Helps teams deepen Azure Databricks delivery capability as the platform becomes more central to enterprise data engineering.

Align labs to your production environment and platform priorities
Add focused exam-readiness reviews and instructor-led practice sessions
Extend into project-specific architecture or delivery coaching

Credentials

Certification & official source

•DP-750T00

Aligned to the official Microsoft Learn course and learning path for this program.

View Official Microsoft Learn Page

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.

Program brief (PDF)View Official Microsoft Learn Page

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.”

Banking & Finance

Representative Enterprise Banking Team

The focus was not just on tooling knowledge, but on helping teams work from a shared operating model as they adopted a more modern data platform.

Clearer platform operating model across teams
Improved confidence in modern data stack adoption

Read engagement

Healthcare

Representative Healthcare Product Team

The engagement helped product and engineering stakeholders move from interest in AI to clearer implementation choices, security expectations, and prototyping discipline.

Stronger alignment between product and engineering teams
Improved clarity on prototype-to-production requirements

Read engagement

Delivery Capability

Enterprise-grade instruction

View delivery capability profile

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

Plan delivery