Learn Data Engineering

Building the pipelines that deliver reliable data

Data engineers build the systems that collect data, clean it and store it so analysts and applications can use it. Think of them as the people who build the plumbing for data.

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6
Topics covered
5
Step learning path
4
Career roles
Data Engineering: how it works
  • Data Engineer
  • ETL Developer
  • Big Data Engineer
  • Cloud Data Engineer
Why it matters

Why learn Data Engineering?

Every data and AI project depends on good data pipelines.

It combines programming, databases and cloud skills in one career.

It is a strong path if you enjoy building systems that run reliably.

What you will learn in detail

  1. 01

    Advanced SQL & Relational Data Modeling

  2. 02

    Python for Data Engineering & API Ingestion

  3. 03

    Big Data Processing with Apache Spark & PySpark

  4. 04

    Cloud Data Lakehouses (Delta Lake & Medallion Architecture)

  5. 05

    Workflow Orchestration with Apache Airflow

  6. 06

    Data Quality, Testing with dbt & CI/CD DevOps

Roadmap

Your learning path

  1. Learn SQL and Python

  2. Understand data modelling

  3. Build your first pipeline

  4. Move pipelines to the cloud and schedule them

  5. Add testing and monitoring, then build a full project

  6. R2T - Root 2 Tech

    The destination

    Job ready with R2T

Ready to start with Data Engineering?

Tell us about yourself and our team will get in touch.

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