Microsoft Fabric Data Engineer (DP-700)
Ingest, transform, secure, monitor and optimise analytics solutions with Microsoft Fabric lakehouses, warehouses, pipelines and eventstreams. Lessons, exam-style practice, timed mocks and an AI tutor, mapped to every objective of the official exam guide.
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The exam
- Questions
- 50
- Time
- 100 minutes
- Passing score
- 700 on a scale of 1 to 1000
- Exam fee
- Varies by country or region (USD 165 in the United States; the exam page shows no fixed price)
- Valid for
- 1 year; renew for free in the 6 months before expiry by passing an online renewal assessment on Microsoft Learn
- Delivery
- Online proctored or test center, scheduled through Pearson VUE
Official exam page · booked with Microsoft
Every section of the exam guide
3 sections and 49 objectives, in the official weights. Each lesson is mapped to the objectives it covers.
Section 1 · Implement and manage an analytics solution33%
What the exam asks
- Configure Spark workspace settings
- Configure domain workspace settings
- Configure OneLake workspace settings
- Configure data workflow workspace settings
- Configure version control
- Implement database projects
- Create and configure deployment pipelines
- Implement workspace-level access controls
- Implement item-level access controls
- Implement row-level, column-level, object-level, and file-level access controls
- Implement dynamic data masking
- Apply sensitivity labels to items
- Endorse items
- Choose between a pipeline and a notebook
- Design and implement schedules and event-based triggers
- Implement orchestration patterns with notebooks and pipelines, including parameters and dynamic expressions
Lessons
- Workspace settings: Spark, domains, OneLake and data workflows
- Lifecycle management: Git, database projects and deployment pipelines
- Access control: workspace, item, row, column, object and file level
- Dynamic data masking, sensitivity labels and endorsement
- Pipeline or notebook? Schedules and event-based triggers
- Orchestration patterns with notebooks, pipelines, parameters and expressions
Section 2 · Ingest and transform data33%
What the exam asks
- Design and implement full and incremental data loads
- Prepare data for loading into a dimensional model
- Design and implement a loading pattern for streaming data
- Choose an appropriate data store
- Choose between dataflows, notebooks, and T-SQL for data transformation
- Create and manage shortcuts to data
- Implement mirroring
- Ingest data by using pipelines
- Transform data by using PySpark, SQL, and KQL
- Denormalize data
- Group and aggregate data
- Handle duplicate, missing, and late-arriving data
- Choose an appropriate streaming engine
- Process data by using eventstreams
- Process data by using Spark structured streaming
- Process data by using KQL
- Create windowing functions
Lessons
- Full and incremental loads, and preparing a dimensional model
- Choosing a data store and a transformation tool
- Shortcuts, mirroring and ingesting with pipelines
- Transforming data with PySpark, SQL and KQL
- Streaming patterns, engines and eventstreams
- Spark structured streaming, KQL and windowing
Section 3 · Monitor and optimize an analytics solution33%
What the exam asks
- Monitor data ingestion
- Monitor data transformation
- Monitor semantic model refresh
- Configure alerts
- Identify and resolve pipeline errors
- Identify and resolve dataflow errors
- Identify and resolve notebook errors
- Identify and resolve eventhouse errors
- Identify and resolve eventstream errors
- Identify and resolve T-SQL errors
- Optimize a lakehouse table
- Optimize a pipeline
- Optimize a data warehouse
- Optimize eventstreams and eventhouses
- Optimize Spark performance
- Optimize query performance
Lessons
- Monitor ingestion, transformation and semantic model refresh
- Alerts, pipeline errors and dataflow errors
- Resolve notebook, eventhouse, eventstream and T-SQL errors
- Optimize a lakehouse table
- Optimize pipelines, warehouses, eventstreams and eventhouses
- Optimize Spark performance and query performance
28-Day Standard Plan
The default path for engineers who know data engineering but are new to Fabric. It covers all 18 lessons and all six labs in order, with a section drill after each section, then a weak-area day and four full mock exams on days 23 to 27. Labs run on a Fabric trial capacity (or any capacity you may use); delete the lab workspace afterwards. Sit the exam once Mock Exam 3 and Mock Exam 4 are both above 75%. About 1–2 hours a day.
- Day 1Kick-off: workspace settings
- Day 2Lifecycle: Git, database projects, deployment pipelines
- Day 3Access control, layer by layer
- Day 4Masking, labels, endorsement and the first lab
- Day 5Pipeline or notebook, schedules and triggers
- Day 6Orchestration patterns and the second lab
- Day 7Section 1 drill and review
- … and 21 more days, with mock exams at the end
Sample questions
Written for practice in the style of the real exam: never questions from the real exam.
Sample question 1
A solution needs to run a notebook, then a stored procedure, send an email on failure and retry the notebook twice before failing. Which item should orchestrate the steps?
- AA notebook calling notebookutils.notebook.run for each step
- BA data pipeline
- CAn eventstream
- DA Dataflow Gen2
Show the answer
B. Use a pipeline as the outer orchestrator for mixed activities: Notebook, Script or Stored procedure, notifications, retries, timeouts and dependency conditions.
Sample question 2
A Spark session has spark.sql.parquet.vorder.default set to true. A write uses the DataFrame option parquet.vorder.enabled = false. What is the result?
- AThe files are written without V-Order, because the explicit write option always wins
- BThe write fails because the settings conflict
- CThe files are written with V-Order, because the session setting takes precedence
- DThe write is V-Ordered only for the first partition
Show the answer
C. When V-Order is enabled at the session level, all Parquet writes in that session use it, including Delta writes where the write option or table property is false.
About this exam
What does the exam cost, and how long is it?
The price depends on the country or region where you test (the United States price shown in this course is USD 165). The exam time is 100 minutes; plan about 120 minutes at the desk including instructions. Microsoft does not publish the number of questions.
Is the exam open book?
Not in the usual sense. You cannot bring notes or use search engines, but on role-based exams you can open Microsoft Learn (learn.microsoft.com) from the left navigation panel. Q&A, practice assessments and your profile are blocked, the clock keeps running, and no extra time is added. Use it for a specific detail.
Online proctored or test center?
Both go through Pearson VUE. Online needs a clean room, a good connection, a system test, ID and room photos, and recording; community reports say some proctors are unsure about Learn access, so know the rule. A test center avoids the technical risk and the facial comparison, at the cost of travel.
Are there case studies and labs?
The exam can include case studies and interactive components; Microsoft does not list formats in advance and may remove labs at any time. Try the exam sandbox to see each type. Prepare for both by doing this course's labs.
Do I need to be able to write PySpark, T-SQL and KQL?
Yes. The study guide expects skill with SQL, PySpark and KQL. You rarely write long programs, but you need to read them, spot the bug, and choose the right function or statement.
Does the exam cover Preview features?
Mostly generally available features. Microsoft says the exam may include Preview features if they are commonly used. This course labels Preview items such as interval-based schedules, warehouse data clustering and the eventstream SQL operator.
What is the passing score?
700 on a scale of 1 to 1,000. It is a scaled score, so you cannot convert it into a number of correct answers. Answer every question because guessing has no penalty.
What do I do when I fail?
You can retake 24 hours after the first failure, then wait 14 days between later attempts, up to five attempts in 12 months. Your score report shows a bar chart per skill area; use it to pick the section drills to redo.
How long is the certification valid and how do I renew?
It is valid for one year. You can renew at no cost by passing an online renewal assessment on Microsoft Learn in the six months before it expires.
Do I need a paid capacity for the labs?
A Fabric trial capacity is enough for most labs, but trial capacities have limits (for example no X-Large or XX-Large Spark nodes) and expire. Delete the lab workspace when you finish. Mirroring, eventstreams and some features have extra requirements (eventstreams need at least an F4 or a trial).
See where you stand in 8 minutes
Ten questions from this course, weighted like the real exam, with your score by section and a rough chance of passing.