Data Engineering Training Course

  • Data Engineering Training Course
  • Germany - Berlin

Data Engineering Training Course

Course Category : Data Management

An advanced training programme focused on designing, building, and managing modern data infrastructures that support advanced analytics and data-driven decision-making across organisations.
Duration: 5 Days
Level: Advanced.

Starts On

12 - October - 2026

Ends On

16 - October - 2026

Location

Germany - Berlin

Language

English

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View Course Introductory PDF

Targeted Audience

  • Data Engineers
  • Data Analysts and BI Professionals
  • Data and Information Managers
  • Digital Transformation Specialists
  • Database Administrators
  • IT Managers
  • Analytics and Solution Developers
  • Big Data Project Professionals

Targeted Skills

  • Modern Data Architecture Design
  • Data Pipeline Fundamentals
  • Data Warehouse and Data Lake Management
  • Data Governance and Quality Management
  • Big Data Technologies Understanding
  • Enterprise Data Lifecycle Management

Expected Outcomes

  • Understand the core principles of modern data engineering.
  • Identify key components of enterprise data architectures.
  • Comprehend data pipeline design and management approaches.
  • Apply data governance and quality concepts.
  • Understand big data and cloud-based data technologies.
  • Support analytics and digital transformation initiatives through data engineering practices.

Training Topics Index

  • Evolution of data engineering
  • Data ecosystem components
  • Enterprise data lifecycle
  • Data engineer roles and responsibilities

  • Data pipeline concepts
  • Data ingestion methods
  • Data integration and transformation
  • Data flow monitoring and quality

  • Data warehousing concepts
  • Modern data lake architectures
  • Enterprise storage models
  • Structured and unstructured data management

  • Big data fundamentals
  • Large-scale data processing
  • Cloud-based data architectures
  • Scalability and performance considerations

  • Data governance principles
  • Data quality management
  • Data security and privacy
  • Compliance and enterprise policies