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Data Engineer

Build the pipelines that move, clean, and store data so others can use it.

datasqlpythondatabasesinfrastructure
Start with: STEM Foundations: The Universal Skill StackTake the career survey

Career facts

Preparation
Considerable preparation needed · most need a bachelor's degree
Ways in
  • Bachelor's degree
  • Industry certification
  • Portfolio of projects
Field
Software, data & cyber

About this career

Data engineers design the systems that collect data from many sources, clean and reshape it, and load it into warehouses and databases that analysts and data scientists can trust. The work mixes software engineering with databases: Python and SQL, data modeling, scheduled jobs, and running it all reliably in the cloud. A good fit if you like building infrastructure and care about getting the details of data right.

Learning path

Take these courses in order, from beginner to mid-level.

  1. Step 1: STEM Foundations: The Universal Skill Stack

    The shared base every STEM career uses: working with numbers and units, testing ideas fairly, handling data and code, and explaining your work.

    Level: Beginner4 modules · 12 lessons · 7h 18mAlso used in 34 other careers

  2. Step 2: Digital Literacy for Tech & STEM Work

    The everyday computer, internet, safety and AI skills every tech and STEM job assumes you already have.

    Level: Beginner4 modules · 12 lessons · 6h 8mAlso used in 34 other careers

  3. Step 3: Professional Communication & Teamwork

    Write clear emails and documents, present and run meetings, work well on teams, and navigate résumés, interviews and networking.

    Level: Beginner4 modules · 12 lessons · 7h 24mAlso used in 34 other careers

  4. Step 4: Math for Tech & STEM

    The practical math behind tech and STEM work: numbers, algebra, functions, geometry, logic and counting, with short code exercises.

    Level: Beginner5 modules · 15 lessons · 7h 32mAlso used in 34 other careers

  5. Step 5: Git & the Command Line

    Use the terminal with confidence, track your work with Git, and collaborate on GitHub with pull requests.

    Level: Beginner3 modules · 9 lessons · 5h 57mAlso used in 15 other careers

  6. Step 6: Python Fundamentals

    Learn to program in Python from zero: values, decisions, loops, functions, data structures, files, modules and a small data project.

    Level: Beginner5 modules · 15 lessons · 9h 53mAlso used in 22 other careers

  7. Step 7: SQL Fundamentals

    Query, summarise, join and change data in a relational database with SQL, practised in your browser.

    Level: Beginner4 modules · 12 lessons · 5h 44mAlso used in 11 other careers

  8. Step 8: Statistics Fundamentals

    Describe data, reason with probability, and draw honest conclusions from samples, with short fill-in-the-blank Python exercises.

    Level: Beginner4 modules · 12 lessons · 6h 50mAlso used in 14 other careers

  9. Step 9: Networking Fundamentals

    Learn how data moves between computers: layers, IP addresses and subnets, ports, DNS, DHCP, HTTPS, and the tools to troubleshoot it.

    Level: Beginner3 modules · 9 lessons · 5h 11mAlso used in 8 other careers

  10. Step 10: Foundations for Software, Data, Design & Tech Education Careers

    Understand tech roles and career ladders, pick a realistic learning route, build portfolio evidence, and navigate postings, interviews and your first 90 days.

    Level: Beginner3 modules · 9 lessons · 7h 22mAlso used in 20 other careers

  11. Step 11: Intro to Data Analysis with Python

    Load, clean, reshape and explore real data with Python and pandas, then turn the results into clear findings.

    Level: Intermediate4 modules · 13 lessons · 12h 55mAlso used in 10 other careers

  12. Step 12: Data Structures & Algorithms

    Measure efficiency with Big-O, then use searching, sorting, hash maps, stacks, linked lists, trees, graphs and dynamic programming in Python.

    Level: Intermediate4 modules · 12 lessons · 7h 37mAlso used in 7 other careers

  13. Step 13: SQL for Analysis

    Go beyond the basics with subqueries, CTEs, window functions and the analytics patterns analysts use every day, practised in your browser.

    Level: Intermediate4 modules · 12 lessons · 7h 18mAlso used in 5 other careers

  14. Step 14: Linux Administration

    Run a Linux server with confidence: users and permissions, services, packages, logs, SSH keys, bash scripts and scheduled jobs.

    Level: Intermediate3 modules · 9 lessons · 10h 12mAlso used in 6 other careers

  15. Step 15: Cloud Fundamentals

    Learn how the public cloud works: service models, regions, shared responsibility, compute, storage, networking, IAM, secrets and cost control, using free tiers only.

    Level: Intermediate3 modules · 10 lessons · 5h 57mAlso used in 3 other careers

  16. Step 16: Database Administration

    Design, tune, operate and secure production databases: normalisation, indexing, backups, replication, access control, monitoring and safe migrations.

    Level: Mid-level4 modules · 12 lessons · 7h 40mAlso used in 1 other career

Skills you'll build

Python

A beginner-friendly, general-purpose language popular in data, AI, and scripting.

SQL

The language for asking questions of relational databases. Used everywhere.

Pandas

The Python library data analysts and scientists use to clean and explore tabular data.

Data Structures

How data is organized in memory — lists, trees, graphs, hash maps. Underpins everything.

Cloud Fundamentals

Core concepts of cloud providers (AWS, GCP, Azure): compute, storage, networking, IAM.

Docker

Containerization tool that packages applications so they run the same everywhere.

Git

The version-control tool every software team uses to track and merge changes.

Free resources to get started

Hand-picked courses and reading from trusted free providers.

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