Data Engineer Accelerator (AWS/Microsoft Fabric)

DMT Data Engineer Accelerator™

Learn. Build. Engineer. Transform Data. Drive Impact.

Two Career Pathways. One Powerful Program. Your Future in Data Engineering Starts Here!

Don’t just learn data engineering. Learn to design, build, automate, secure, and manage the data infrastructure that powers today’s digital economy!

At Dynamic Mentoring Tech (DMT), we’re preparing the next generation of Data Engineers through hands-on technical training, expert mentorship, industry-recognized certification preparation, and real-world engineering projects.

Our DMT Data Engineer Accelerator™ is an intensive, 10-week, career-focused workforce development program designed to equip aspiring data professionals with the technical foundations, cloud engineering capabilities, and practical experience needed to pursue opportunities in today’s rapidly evolving data engineering industry.

From Linux, Python, and SQL to enterprise data pipelines, cloud data platforms, data lakes, data warehouses, and analytics, students learn how to transform raw information into secure, scalable, and business-ready data solutions.

Whether you’re a college student, career changer, database administrator, aspiring IT professional, or experienced technician looking to advance your career, this program provides a structured pathway into modern data engineering.

Two Specialized Data Engineering Career Tracks

Choose your cloud platform. Master the tools. Build your future.

Students begin with essential data engineering foundations before specializing in one of two industry-leading cloud data platforms.

Track 1 — AWS Data Engineering Accelerator

Build Scalable Data Solutions in the AWS Cloud.

The AWS Data Engineering Track prepares students to design, develop, automate, and maintain cloud-based data pipelines and analytics infrastructure using Amazon Web Services.

Students gain practical experience with:

AWS Cloud Fundamentals and Architecture
Data Ingestion and Storage using Amazon S3 and Amazon Redshift
Data Processing with AWS Glue and Amazon EMR
Data Transformation using Python, PySpark, and SQL
ETL/ELT Pipeline Design and Orchestration
Data Analytics and Visualization using Amazon QuickSight
Infrastructure as Code using Terraform
Data Security, Governance, and Access Management
Performance Optimization and Troubleshooting
Real-World AWS Data Engineering Projects

Industry Certification Pathway:

CompTIA DataSys+ — Foundational database administration, data management, security, and operations
AWS Certified Data Engineer – Associate — Specialized AWS data engineering knowledge and skills

Track 2 — Microsoft Fabric Data Engineering Accelerator

Design Modern Enterprise Data Solutions with Microsoft Fabric.

The Microsoft Fabric Data Engineering Track prepares students to build and manage modern enterprise data solutions using Microsoft’s unified analytics and data engineering platform.

Students gain practical experience with:

Microsoft Fabric Architecture and Core Components
Data Ingestion and Lakehouse Architecture
Data Transformation using Dataflows and Pipelines
Apache Spark and Notebook-Based Data Processing
SQL for Data Engineering
Data Warehousing and Data Modeling
Microsoft Power BI Integration and Analytics
Data Security, Governance, and Compliance
Pipeline Performance and Optimization
Real-World Microsoft Fabric Data Engineering Projects

Industry Certification Pathway:

CompTIA DataSys+ — Foundational database administration, data management, security, and operations
Microsoft Certified: Fabric Data Engineer Associate (DP-700) — Specialized Microsoft Fabric data engineering knowledge and skills

CompTIA DataSys+ serves as a foundational milestone in DMT’s learning pathway. It is not an official prerequisite for the AWS or Microsoft certification examinations.

Three Training Modules. Ten Weeks. Real Engineering Experience.

Our structured curriculum progressively develops students’ skills from foundational programming and data concepts to designing and presenting a complete enterprise data engineering solution.

Module 1 — Data Engineering Foundations (Weeks 1–4)

Build the technical foundation every Data Engineer needs.

Students develop essential skills in Linux, Python, SQL, and data management.

What You’ll Learn:

Linux for Data Engineers
Python Programming for Data Engineering
Data Automation and Scripting
Data Engineering Fundamentals
Data Concepts and Modeling
SQL Fundamentals and Query Development
File Systems and Data Formats (CSV, JSON, Parquet)
Version Control using Git

Student Outcome: Develop the foundational technical skills required to work with data, write automation scripts, query databases, and prepare information for processing and analysis.

Module 2 — Cloud Data Engineering Specialization (Weeks 4–9)

Choose AWS or Microsoft Fabric and begin building real-world data solutions.

Students apply their foundational knowledge to their selected cloud data engineering platform.

What You’ll Learn:

AWS or Microsoft Fabric Platform Architecture
Data Pipeline Design and Development
ETL/ELT Engineering
Data Warehousing and Lakehouse Architecture
Data Processing and Transformation
Data Analytics and Visualization
Data Security, Governance, and Compliance
Performance Optimization
Real-World Data Engineering Case Studies

Student Outcome: Design, develop, and troubleshoot cloud-based data pipelines using your selected platform.

Module 3 — Enterprise Data Engineering Capstone & Portfolio (Week 10)

Bring everything together. Build an enterprise data engineering solution.

Students complete a comprehensive capstone project that demonstrates their ability to design, implement, automate, and document a practical data engineering workflow.

What You’ll Build:

An end-to-end data engineering solution
A functional cloud-based data pipeline
Data ingestion and transformation workflows
Cloud data storage and processing components
Data analytics and visualization outputs
Security and access management configurations
Technical documentation and architecture diagrams
A GitHub portfolio showcasing project deliverables

Students conclude the program with a technical project presentation and career-readiness activities.

Student Outcome: Complete a documented, demonstrable data engineering capstone project that can be discussed during technical interviews and shared with prospective employers.

What Will You Build? Real-World Data Engineering Projects.

At DMT, students don’t just study cloud data services. They learn how to build the systems that collect, process, transform, and deliver enterprise data.

Throughout the program, students develop practical engineering experience through hands-on labs and projects.

Student Project Deliverables

1. Linux & Python Data Engineering Environment

Configure a Linux development environment and develop Python scripts for data processing, file handling, automation, and data validation.

2. SQL Data Processing & Transformation

Build SQL queries and transformation workflows to clean, organize, join, aggregate, and prepare structured data.

3. Cloud Data Ingestion Pipeline

Create an automated data ingestion workflow using AWS or Microsoft Fabric to collect and store data from supported sources.

4. Enterprise Data Lake or Lakehouse

Design and configure cloud storage and processing components to support scalable data engineering workflows.

5. ETL/ELT Data Pipeline

Build a complete pipeline that extracts, loads, transforms, and prepares data for downstream analytics.

6. Data Security & Governance

Implement appropriate access controls, permissions, and data protection practices within the selected cloud platform.

7. Data Analytics & Visualization

Prepare processed datasets for reporting and create dashboards or analytical outputs using supported visualization tools.

8. Enterprise Data Engineering Capstone

Design, deploy, test, document, and present an integrated cloud data engineering solution.

Your Final Deliverable: An Employer-Ready Data Engineering Portfolio

Students who successfully complete the required projects will develop a technical portfolio featuring:

Cloud data architecture diagrams
Python and SQL engineering projects
ETL/ELT pipeline implementations
Data ingestion and transformation workflows
AWS or Microsoft Fabric cloud configurations
Data security and governance examples
Data analytics and visualization projects
GitHub repositories with documented source code
Final enterprise data engineering capstone presentation

These deliverables provide tangible examples of students’ technical capabilities to demonstrate during job interviews and professional career development activities.

Prepare for High-Demand Data Engineering Careers

The skills developed throughout this program support career pathways such as:

AWS Data Engineer
Microsoft Fabric Data Engineer
Cloud Data Engineer
Data Pipeline Engineer
ETL/ELT Engineer
Big Data Engineer
Analytics Engineer
Data Analytics Specialist
Data Platform Engineer

Students build a foundation for pursuing entry-level and developing professional opportunities. More advanced positions may require additional industry experience and specialized technical training.

What You’ll Receive with DMT

Real Skills. Real Projects. Real Opportunities.

The DMT Data Engineer Accelerator combines technical instruction, hands-on engineering, and workforce development support.

Program Benefits Include:

Live Instructor-Led Sessions: Structured technical instruction and guided learning.
Hands-On Labs & Projects: Practice using real tools, cloud services, and engineering workflows.
Industry Certification Preparation: Structured learning aligned with CompTIA DataSys+ and your selected cloud platform certification.
Expert Mentorship: Guidance from experienced technology and engineering professionals.
Resume & LinkedIn Optimization: Professional career branding and resume development.
Interview Preparation: Mock interviews, technical interview practice, and professional coaching.
Career Coaching & Job Placement Support: Assistance with career planning, job search strategies, and employment readiness.
Alumni & Mentor Network: Continued access to the DMT learning community and professional networking opportunities.

Why Choose Dynamic Mentoring Tech?

We Don’t Just Teach Technology. We Develop Technology Professionals.

At Dynamic Mentoring Tech, our mission is to empower individuals through technical education, mentorship, workforce development, and meaningful career opportunities.

Our training model emphasizes practical engineering experience rather than memorizing technical concepts.

Students learn how enterprise data systems operate, how cloud platforms process information, how pipelines are automated, how data is secured, and how analytics solutions support real business decisions.

Through expert mentorship, structured learning, and hands-on projects, we help students develop the technical confidence, problem-solving abilities, and professional readiness needed to pursue careers in the data engineering workforce.

Our philosophy is simple: Certifications demonstrate knowledge. Projects demonstrate capability. Mentorship develops professionals.

Your Future in Data Engineering Starts Here!

Data is one of the most valuable assets in today’s digital economy. Organizations need professionals who can transform that data into reliable, secure, scalable, and actionable information.

Whether you choose AWS Data Engineering or Microsoft Fabric Data Engineering, the DMT Data Engineer Accelerator provides a practical pathway toward building those capabilities.

Choose Your Path. Build Your Future. Transform Data. Drive Impact.

Enroll Today — Start Building Your Data Engineering Future!

Dynamic Mentoring Tech — Building a Brighter Tomorrow!

Website: dynamicmentoring.org
Email: info@dynamicmentoring.org
Phone: 240-695-6564