Microsoft Fabric Data Engineer (DP-700) Training & Certification
- 40 hours of live training aligned with the DP-700 certification exam
- Covers Microsoft Fabric lakehouses, data warehouses, pipelines, notebooks, Eventstreams and Eventhouses
- Covers the complete certification-aligned syllabus (SQL, PySpark and KQL)
- Real-world exposure to enterprise data engineering scenarios on OneLake
- Hands-on labs and real-time project use cases
- Mock tests aligned with the DP-700 exam format
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Microsoft Fabric Data Engineer (DP-700) Training & Certification
Course Overview
Duration
40 HoursStudents Enrolled
800+Certification Aligned
DP-700 (Microsoft Certified: Fabric Data Engineer Associate)Training Mode
Live Instructor-LedHands-On Projects
Real-World ScenariosTrainer Experience
10+ Years Industry ExpertsSession Recordings
10+ Years Industry ExpertsPost-Training Support
2 MonthsWhat You'll Learn
- End-to-end data engineering lifecycle on Microsoft Fabric, from requirement analysis to ingestion, transformation, deployment, monitoring and maintenance
- Hands-on experience with workspace security, item-level and row/column-level access, dynamic data masking, and data governance best practices
- Batch and streaming data ingestion using Fabric Data Factory pipelines, Dataflows Gen2, notebooks, shortcuts, mirroring, Eventstreams and Eventhouses
- Data transformation with T-SQL, PySpark, and Kusto Query Language (KQL) on lakehouses, warehouses, and KQL databases
- Performance optimization of lakehouse tables, pipelines, warehouses, Spark jobs and queries, along with monitoring and troubleshooting
- Lifecycle management with Git integration, deployment pipelines, and database projects across development, test, and production workspaces
Pro Tip: This course is perfect for experienced IT professionals and college graduates looking to transition into Microsoft Fabric data engineering, especially those moving from the retired DP-203 Azure Data Engineer path.
Questions about the course? Contact our support team
Certification Value
Microsoft Fabric Data Engineer Value in the Global Market
Microsoft Fabric is now the core analytics platform behind Microsoft’s data and AI strategy, and the DP-700 certification is the official credential for data engineers who build on it.
Course Overview
Overview
Data is growing faster than most organisations can manage it, and teams no longer want separate tools for ingestion, storage, analytics and reporting. Microsoft Fabric solves this by bringing data engineering, data warehousing, real-time analytics and Power BI together on a single platform built on OneLake. As a data engineer, analyst, or developer, a DP-700 training course shows you how to design, build, and operate these solutions in a real production environment.
By completing the Microsoft Fabric Data Engineer certification course, you will learn how to load and transform data using SQL, PySpark and KQL, orchestrate workloads with Fabric Data Factory pipelines, secure your analytics solution and keep it fast and reliable. The exam, officially called Implementing Data Engineering Solutions Using Microsoft Fabric, leads to the Microsoft Certified: Fabric Data Engineer Associate credential and is split across three equally weighted areas: implementing and managing an analytics solution, ingesting and transforming data, and monitoring and optimizing an analytics solution (30–35% each).
The DP-700 certification also puts you in a strong position in the job market. Microsoft counted 40,000 paid Fabric customers in mid-2026, and employers are already posting dedicated Fabric data engineer roles that ask for lakehouse, Spark, pipeline, and real-time analytics skills. Since the older DP-203 exam has been retired, DP-700 is now the recognised way to prove Azure-era data engineering skills on Microsoft’s latest platform.
Our DP-700 online training combines live instructor-led sessions, guided labs and capstone projects so that you gain hands-on confidence with OneLake, lakehouses, warehouses, Eventstreams and Eventhouses, not just theory. Mock tests modelled on the real exam format help you measure your readiness before test day.
Benefits
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Build Unified Data Platforms Efficiently
DP-700 training helps professionals design lakehouses, warehouses, and real-time pipelines on a single platform, removing the need to stitch together separate tools.
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Master SQL, PySpark and KQL
Participants learn to transform data with the three languages the DP-700 exam expects, which are also the most requested skills in modern data engineering job descriptions.
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Move From DP-203 and Legacy Azure Skills
If you already know Azure Data Factory, Synapse or Databricks, this course maps those skills directly to Fabric so you can upgrade without starting over.
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Work With Batch and Real-Time Data
You gain hands-on practice with batch loading patterns as well as streaming with Eventstreams and Eventhouses, preparing you for AI and analytics projects that depend on fresh data.
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Strong Career Opportunities in Data Engineering
With rapid growth in Fabric adoption, certified professionals can pursue roles such as Fabric Data Engineer, Azure Data Engineer, Analytics Engineer, Data Platform Engineer, and, with experience, Data Architect.
Testimonials
What our Students Say
How to Get the Microsoft Fabric Data Engineer (DP-700) Certification
1 1. Register
- Visit the Microsoft Learn certification page for Microsoft Certified: Fabric Data Engineer Associate
- Register for Exam DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric using a personal Microsoft account
- Exam fee: USD 165 (US pricing); India pricing is shown in INR at checkout, roughly ₹4,800–₹4,900 plus applicable taxes [confirm at publishing]
2 Examination Details
- Passing score: 700 on a scale of 1,000
- Question types: case studies, multiple-choice questions, and interactive or drag-and-drop items
- Duration: about 100 minutes
- Skills measured: Implement and manage an analytics solution (30–35%), Ingest and transform data (30–35%), Monitor and optimize an analytics solution (30–35%)
3 Examination Schedule
- Complete the exam fee payment
- Select a Pearson VUE test center or opt for online proctored mode
- Flexible scheduling with rescheduling options
- If you do not pass, you can retake the exam after 24 hours, with longer waiting periods for later attempts
4 Certification Maintenance
- Earn a digital Microsoft Certification and shareable badge (LinkedIn, resume, email)
- The certification is valid for one year and can be renewed at no cost by passing a short online assessment on Microsoft Learn
- Globally recognised and valued across the industry
Who Can Take Up the Microsoft Fabric Data Engineer (DP-700) Training & Certification
Data Engineers and ETL Developers
Professionals building pipelines in Azure Data Factory, Synapse, SSIS or Databricks can move their skills to Fabric and validate them with an up-to-date credential.
Data Analysts and BI Developers
Power BI professionals who want to go beyond dashboards and learn how to prepare, model, and load data in lakehouses and warehouses.
Database Administrators and SQL Developers
SQL professionals can extend their T-SQL expertise into Spark, Delta tables, and real-time analytics.
Cloud and Azure Professionals
Azure administrators and cloud engineers who want to specialise in data platforms and AI-ready data foundations.
Freshers and Career Switchers
Graduates with basic SQL and Python knowledge who want an entry point into one of the fastest-growing data roles.
Who Can Take Up the Microsoft Fabric Data Engineer (DP-700) Training & Certification
- Information Technology
- Healthcare
- Manufacturing
- Construction
- Finance & Banking
IT Professional Certification
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Frequently Asked Questions
DP-700 is the exam for the Microsoft Certified: Fabric Data Engineer Associate credential. It tests your ability to implement data engineering solutions on Microsoft Fabric, including ingesting and transforming data, securing and managing an analytics solution, and monitoring and optimizing performance. Candidates are expected to work with SQL, PySpark, and KQL. The certification is aimed at data engineers who build and operate production analytics platforms.
DP-700 suits data engineers, ETL developers, analytics engineers, SQL developers, and cloud professionals who work with data pipelines. It is especially useful for people who previously worked toward DP-203 or who use Azure Data Factory, Synapse, or Databricks and want to move to Fabric. Freshers with solid SQL fundamentals can also take it, although hands-on practice in Fabric labs is strongly recommended before the exam.
DP-700 focuses on the data engineer role: pipelines, loading patterns, Spark, KQL, streaming, security and optimization. DP-600 (Fabric Analytics Engineer Associate) leans more toward analytics assets such as semantic models, DAX, and reporting-ready data. If your day-to-day work is building and operating pipelines and lakehouses, start with DP-700. If you build semantic models and reports, DP-600 is the better first step. Many professionals eventually earn both.
In practice, yes. Microsoft retired DP-203 (Azure Data Engineer Associate) on March 31, 2025, and directed new data engineering candidates to Fabric-based certification. DP-700 covers the same professional role, but on Microsoft Fabric rather than separate Azure services. Existing DP-203 skills such as Data Factory, Spark, and SQL transfer well, so experienced engineers can upskill faster than beginners.
DP-700 is an intermediate-level exam that rewards practical experience. The difficulty comes from its breadth: you need SQL, PySpark, and KQL, plus Fabric-specific features such as shortcuts, mirroring, Eventstreams, and Eventhouses. Most learners with a data background prepare for four to eight weeks, mixing structured training, hands-on labs, and timed practice tests. Anyone new to Spark or KQL should allow extra time.
You do not need to be a software developer, but some coding is required. SQL is essential, and basic Python helps with PySpark notebooks. KQL is newer for most learners, so our course teaches it from the beginning. Fabric also offers low-code tools such as Dataflows Gen2 and pipelines for many ingestion tasks, which makes the platform friendly for people moving from ETL or BI backgrounds.
The standard exam price in the United States is USD 165. Microsoft adjusts prices by country, and in India the fee is shown in rupees at checkout, roughly ₹4,800–₹4,900 plus taxes at the time of writing. Students, Microsoft partners, and event attendees can sometimes get discounts or vouchers, so always check the price shown on the Microsoft Learn scheduling page before booking.
The exam lasts about 100 minutes and includes case studies, multiple-choice questions and interactive items. The passing score is 700 out of 1,000. The three skill areas, implementing and managing an analytics solution, ingesting and transforming data, and monitoring and optimizing an analytics solution, each carry 30–35% of the exam. If you fail, you can retake it after 24 hours.
Salaries vary by experience, company type, and city. In India, data engineers commonly earn between ₹7L and ₹14L at entry level, ₹16L to ₹26L mid-career, and ₹28L or more at senior level; Fabric-specific roles often range from ₹9L to ₹28L. In the US, average data engineer base pay is about 135K, and Fabric data engineer job postings average around $121K per year. Certification alone does not set your pay, but it strengthens your profile.
Typical roles include Microsoft Fabric Data Engineer, Azure Data Engineer, Analytics Engineer, ETL/ELT Developer, Data Platform Engineer, BI Engineer, and Cloud Data Engineer. With experience, you can move to Senior Data Engineer, Data Architect, or Data Platform Lead positions. Consulting firms and Microsoft partners are especially active in hiring Fabric-skilled engineers as customers migrate from Synapse, Data Factory, and Power BI Premium.
OneLake is Fabric’s single, tenant-wide data lake, often described as the OneDrive for data. A lakehouse stores structured and unstructured data in OneLake and lets you query it with Spark or SQL. Delta tables are the default open table format, offering ACID transactions, schema enforcement, and time travel on top of Parquet files. Understanding how these three fit together is the foundation of almost every DP-700 scenario.
Use a lakehouse when you work with large, varied data and want Spark-based engineering and flexible schemas. Use a warehouse when your team prefers T-SQL, needs multi-table transactions, and serves structured analytics workloads. Use an Eventhouse (KQL database) for high-volume streaming and time-series data that needs very fast queries. Choosing the right store for a given scenario is a skill the exam tests repeatedly.
Choose projects that show different patterns instead of repeating the same pipeline. A strong portfolio could include a medallion lakehouse built from raw files, an incremental load pipeline with a watermark, a mirrored database feeding a warehouse, a real-time dashboard fed by an Eventstream into an Eventhouse, and a monitoring and optimization case study. For each project, document the problem, architecture, design choices and measurable results.
Expect scenario questions on loading patterns (full vs incremental), choosing between lakehouse and warehouse, shortcuts versus mirroring, PySpark and T-SQL transformations, handling late or duplicate data, pipeline failures, Delta table optimization and workspace security. Interviewers also like to ask how you would monitor a pipeline in production and reduce capacity consumption, so be ready to explain your design decisions and trade-offs clearly.
Yes. TechVibz Academy offers career support including resume guidance, interview preparation and mock interviews, along with post-training support and lifetime access to session recordings.
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