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  1. Programs
  2. Microsoft Certified: Azure Databricks Data Engineer Associate (beta)

Microsoft Certified: Azure Databricks Data Engineer Associate (beta)

Microsoft

Certification

Become a contributor for free to openly demonstrate student outcomes, industry alignment & eligibility criteria.

Demonstrate expertise in integrating and modeling data, building and deploying optimized pipelines, and troubleshooting and maintaining workloads in Azure Databricks.

Cost

$165Show moreShow less

Format

Hybrid

Eligibility Calculator

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Program Pathways

Credentials this program stacks toward

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Program Details

Detailed information about this program

As a candidate for this Microsoft Certification, you should have subject matter expertise in integrating and modeling data, building and deploying optimized pipelines, and troubleshooting and maintaining workloads in Azure Databricks. You should also have experience applying data quality and data governance best practices in Unity Catalog. You need to know how to ingest and transform data by using Structured Query Language (SQL) and Python. You need experience with software development lifecycle (SDLC) practices, including Git. Additionally, you should be familiar with Microsoft Entra, Azure Data Factory, and Azure Monitor. Your responsibilities for this role include: - Setting up and configuring an Azure Databricks environment. - Securing and governing Unity Catalog objects. - Preparing and processing data. - Deploying and maintaining data pipelines and workloads. You work closely with administrators, platform architects, solution architects, data scientists, and data analysts to design, deploy, and secure data engineering solutions by using Azure Databricks. You will have 100 minutes to complete this assessment. Exam policy This exam will be proctored. You may have interactive components to complete as part of this exam. To learn more about exam duration and experience, visit: Exam duration and exam experience. If you fail a certification exam, don’t worry. You can retake it 24 hours after the first attempt. For subsequent retakes, the amount of time varies. For full details, visit: Exam retake policy. Assessed on this exam - Set up and configure an Azure Databricks environment - Secure and govern Unity Catalog objects - Prepare and process data - Deploy and maintain data pipelines and workloads Need accommodations? We offer a variety of accommodations to support you. This exam is offered in the following languages: English

Requirements

What you need to earn this credential

No requirements listed.

Financial Aid

Eligible funding programs

No funding information available.

Scholarships

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Locations

Where this program is offered

No locations specified.

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Related Programs

Programs related to this one

No related programs.

Skills & Competencies

Skills developed through this program

  • Set up and configure an Azure Databricks environment
  • Select and configure compute in a workspace
  • Secure and govern Unity Catalog objects
  • Create and organize objects in Unity Catalog
  • Prepare and process data
  • Ingest and transform data
Career Pathways

Occupations this program prepares you for

  • Database Architects15-1243.00
What You'll Learn

Key competencies developed through this program

Auto-populated·from NSX Competency Framework

Mastery: developing (Level 2)(based on Certification)

  • Database architectures — develop and document end-to-end designs for moderately complex systems with limited oversight in an enterprise setting.
  • Stakeholder collaboration — participate actively in cross-functional sessions with system architects and design analysts to translate business needs into data requirements.
  • Data models — design normalized relational and dimensional models including metadata tables and views for business application support.
  • Database security — implement role-based access controls, encryption policies, and audit logging in accordance with organizational security standards.
  • Performance tuning — analyze query execution plans and apply indexing strategies, including function-based indexes, to optimize database response times.
  • Architectural strategies — apply layered modeling and design approaches across development lifecycle phases to satisfy documented business requirements.
  • Database application components — build data partitions, global temporary tables, and stored procedures to enable efficient access to enterprise data structures.
  • Product integration — develop and test methods for connecting disparate database products and middleware within a multi-system environment.
  • Database development standards — enforce team-level coding and design conventions through code reviews and written guidelines.
  • ERP and enterprise software — configure and extend commercial database schemas to align with organization-specific operational workflows.

Some details on this page are auto-populated from public workforce data sources: O*NET (opens in new tab), BLS (opens in new tab), College Scorecard (opens in new tab), DOL Training Provider Results (opens in new tab), NSX (opens in new tab). Provided in partnership with LER.me Career Intelligence.

Student Outcomes

Performance metrics for this program

Completion Rate
Not reported
Placement Rate
Not reported