Skymirror Academy

Data Engineering Program

Master the design, build, and maintenance of robust data infrastructure and pipelines for modern data-driven organizations.

Program Overview

Duration & Format

  • 24 weeks (6 months)
  • Aspiring data engineers, developers transitioning to data engineering
  • Prerequisites: Basic programming (Python preferred), database understanding

What You'll Master

  • Scalable data pipeline design and implementation
  • Cloud platforms (AWS, GCP, Azure) for data engineering
  • Real-time and batch data processing systems
  • Data quality monitoring and governance

Program Investment

Standard Price: €2,990
Early-Bird Price: €2,590
Save €400 with early registration (limited time)

What's Included

  • 24 week intensive program
  • 24/7 mentor-assisted learning
  • Real-time and batch processing projects
  • Cloud platform access (AWS/GCP/Azure)
  • Blockchain-verified certification
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View Detailed Syllabus

Detailed Curriculum

Module 0 – Data Engineering Foundations

Week 0

Establish foundational knowledge and set up development environment.

Topics Covered:

  • • Data engineering role and responsibilities
  • • Modern data stack overview
  • • Development environment setup
  • • Git workflows for data engineering

Projects & Assessments:

  • • Environment setup verification
  • • Git repository creation
  • • Data Engineering Fundamentals Quiz

Module 1 – Python & SQL Foundations

Weeks 1–2

Master Python and SQL for data engineering tasks.

Topics Covered:

  • • Advanced Python for data engineering
  • • SQL for data engineering
  • • Database design principles
  • • Data modeling techniques

Projects & Assessments:

  • • Build data processing script with Python and SQL
  • • Python & SQL Proficiency Quiz

Module 2 – Data Pipeline Fundamentals

Weeks 3–4

Understand ETL/ELT concepts and build basic pipelines.

Topics Covered:

  • • ETL vs ELT design patterns
  • • Data extraction methods
  • • Transformation patterns
  • • Loading strategies

Projects & Assessments:

  • • Build end-to-end ETL pipeline
  • • Data Pipeline Concepts Quiz

Module 3 – Apache Airflow & Workflow Orchestration

Weeks 5–6

Master workflow orchestration using Apache Airflow.

Topics Covered:

  • • Airflow architecture & concepts
  • • Building DAGs and operators
  • • Scheduling & monitoring workflows
  • • Best practices for production

Projects & Assessments:

  • • Create complex data workflows with Airflow
  • • Airflow Orchestration Quiz

Module 4 – Cloud Data Platforms

Weeks 7–9

Work with cloud-native data services across major platforms.

Topics Covered:

  • • AWS data engineering stack
  • • GCP data engineering tools
  • • Azure data platform
  • • Cloud storage and managed databases

Projects & Assessments:

  • • Build cloud-native data pipeline
  • • Cloud Platforms Quiz

Module 5 – Stream Processing & Real-time Data

Weeks 10–11

Process streaming data in real-time with modern frameworks.

Topics Covered:

  • • Stream processing concepts
  • • Apache Kafka fundamentals
  • • Real-time data processing
  • • Event-driven architecture

Projects & Assessments:

  • • Build real-time data streaming pipeline
  • • Stream Processing Quiz

Module 6 – Data Warehousing & Analytics

Weeks 12–14

Design and implement modern data warehouses for analytics.

Topics Covered:

  • • Data warehouse design principles
  • • Dimensional modeling techniques
  • • Modern data warehouse architectures
  • • Analytics optimization

Projects & Assessments:

  • • Design and implement a data warehouse
  • • Data Warehousing Quiz

Module 7 – Big Data Technologies

Weeks 15–16

Work with big data processing frameworks and architectures.

Topics Covered:

  • • Big data fundamentals
  • • Apache Spark for data engineering
  • • Data lake architecture
  • • Distributed computing concepts

Projects & Assessments:

  • • Process large datasets with Spark
  • • Big Data Technologies Quiz

Module 8 – Data Quality & Governance

Weeks 17–18

Implement data quality and governance practices for enterprise environments.

Topics Covered:

  • • Data quality frameworks
  • • Data testing & validation
  • • Data governance & compliance
  • • Monitoring and alerting

Projects & Assessments:

  • • Implement data quality monitoring system
  • • Data Quality & Governance Quiz

Module 9 – DevOps for Data Engineering

Weeks 19–20

Apply DevOps practices to data engineering workflows.

Topics Covered:

  • • DataOps principles
  • • CI/CD for data pipelines
  • • Infrastructure as code
  • • Containerization and monitoring

Projects & Assessments:

  • • Implement CI/CD pipeline for data project
  • • DataOps Quiz

Module 10 – Capstone Data Engineering Project

Weeks 21–24

Build and deploy a comprehensive data engineering solution.

Project Requirements:

  • • End-to-end data engineering solution
  • • Real-world data sources and scenarios
  • • Industry-standard tools and practices
  • • Comprehensive documentation

Deliverables:

  • • Complete data engineering project
  • • Peer review & technical feedback
  • • Self-assessment & knowledge integration
  • • Portfolio-ready project showcase

Career Outcomes

Industry Connections

  • • Guest lectures from data engineering professionals
  • • Industry case studies and real-world scenarios
  • • Networking with data engineering community

Portfolio Development

  • • GitHub portfolio with documented projects
  • • Technical blog posts and knowledge sharing
  • • Open-source contributions

Job Readiness

  • • Technical interview preparation
  • • Resume and LinkedIn optimization
  • • Salary negotiation strategies