The Microsoft Fabric Data Engineer Professional Certificate prepares you for data engineering roles, where you will build and manage data workflows in modern data environments. Organizations rely on data engineers to move data across systems, prepare it for analysis, and ensure data platforms operate reliably and securely.
Designed for aspiring data engineers and data professionals, this program builds practical capability to understand platform architecture, ingest and transform data, and manage workflows across a unified data platform.
You will learn to ingest data from multiple sources, structure and transform it for analytical use, and work with data across Fabric components such as Lakehouses and pipelines. You will also develop the ability to prepare analytics-ready datasets, orchestrate workflows, automate data movement, and monitor pipeline execution.
As the program progresses, you will build operational capability by troubleshooting pipeline issues, managing platform performance, applying governance practices, and identifying improvements based on system usage and reliability.
Through applied scenarios and practical activities, you will build and manage data workflows using Microsoft Fabric tools such as OneLake, Dataflows Gen2, pipelines, and Spark-based processing.
By completing this program, you will strengthen your readiness for data engineering roles, with the ability to build, manage, and evaluate data workflows that support analytics and reporting.
Projet d'apprentissage appliqué
You will complete applied projects that reflect common data engineering responsibilities.
In the Data Preparation Project, you will ingest data into a Lakehouse environment, validate its structure, and prepare an analytics-ready dataset for downstream reporting.
In the Data Platform Operations Project, you will review pipelines, performance, and governance configurations within an existing data environment, identify issues, and recommend improvements to support reliability and efficiency.
These projects use realistic data scenarios and platform configurations to develop practical skills in managing data workflows and evaluating platform performance. Each project produces portfolio-ready artifacts that demonstrate your ability to prepare analytics datasets and evaluate data platform operations.
