Data Engineering Career Path

Data engineering has seen explosive growth recently as more industries depend on data to drive key business decisions. Take advantage of the surge in demand by becoming a data engineer with Dataquest.

We designed this career path for beginners with little to no experience who want to become qualified, job-ready data engineers. However, it’s also an excellent option for those already in the data field looking to sharpen their skills and take their career to the next level.

Write real code, and build a career-ready portfolio that employers are looking for — all at your own pace.

  • Build a foundation in Python programming
  • Use PostgreSQL for Data Engineering
  • Build data pipelines

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What You’ll Learn

Wandering through data engineering topics without guidance can be frustrating, confusing, and unmotivating. Dataquest is here to help! With our data engineering path, we guide you through each technical skill required to become a remarkable data engineer.

This career path will teach you all the data skills recruiters look for, plus extras to make you stand out among the sea of tough competition.

  • Python programming
  • Algorithms and Data Structures
  • Building Data Pipelines
  • PostgreSQL for Data Engineering
  • Data structure fundamentals
  • SQL Queries for Data Analysis
  • Optimizing for Large Data Sets using pandas
  • Recursion and Trees
  • NumPy for Data Processing
money in envelope

Data engineers earn on average more than $135K/year as of 2021

bar graph going up

Data engineering interviews grew by 40% in 2020, per Interviewquery

The U.S. Bureau of Labor Statistics projects 31% growth for data science in the next 10 yrs

How Our Data Engineer Career Path Works

Perfect your technical data engineering skills, such as Python programming, data pipelines, and data processing. As you progress through the course, you’ll learn how to implement algorithms and how to work with multi-table databases using SQL. And finally, as you complete the practical coding exercises, you’ll learn key tools like pandas, NumPy, SQLite, MapReduce, and PostgreSQL.

Once you complete our comprehensive program, you’ll have the skills necessary to thrive as a data engineer, and you’ll have a job-ready portfolio to showcase during the interview process.

At Dataquest, we know that navigating a new career path is intimidating, so we’re here to help. We don’t believe in long, uninspiring videos or lectures; instead, we use hands-on and interactive teaching, so you’ll never be bored again. Not only will you learn job-ready skills, you’ll also have the opportunity to put them into practice.

Should you get stuck, or have any questions, we’re here to provide the support you need. Here’s a snapshot of our data engineering career path curriculum:

Enroll in this career path and become a data engineer today!

Data Engineering Career Path Course List

Variables, Data Types, and Lists in Python

Learn the fundamentals of Python programming and data science.

For Loops and Conditional Statements in Python

Learn the fundamentals of Python programming and data science.

Dictionaries, Frequency Tables, and Functions in Python

Learn the fundamentals of Python programming and data science.

Python Functions and Jupyter Notebook

Learn the fundamentals of Python programming and data science.

Python for Data Engineering Intermediate

Learn important tools for your Python data toolbox.

Programming Concepts with Python

Enhance your understanding of how Python works.

Algorithm Complexity

Learn how to assess and implement efficient algorithms with Python.

Elements of the Command Line

Covers what the command line is and why it’s useful.

Text Processing in the Command Line

Covers how to read documentation, and how to use standard streams together with redirection and pipelines to facilitate text processing.

Command Line Intermediate

Builds on your command line beginner skills and covers interacting with the command line in a way that supercharges your data analysis workflow

Git and Version Control

Covers what Git is and how it’s helpful in the context of data analysis and data science work. This will take you from fundamentals to installing Git.

SQL Fundamentals

Learn the basics of working with SQL databases.

Intermediate SQL for Data Analysis

Learn to work with multi-table databases.

Postgres For Data Engineers

Learn about the SQL database PostgreSQL.

Optimizing Postgres Databases

Learn how to optimize your PostgreSQL databases.

Numpy for Data Engineering

Learn how NumPy can be used to optimize your data processing.

Processing Large Datasets In Pandas

Learn how to work with datasets by optimizing your pandas workflow, processing data in batches, and augmenting pandas with SQLite.

Parallel Processing

Learn parallel processing and MapReduce.

Data Structures Fundamentals

Learn the fundamentals of data structures — Linked Lists, Queues, Stacks and Dictionaries, etc.

Recursion and Trees

Learn about recursion and how it applies to tree data structures, and how tree data structures are used to speed up processing of data analysis tasks.

Building a Data Pipeline

Learn how to build a Python data pipeline from scratch.

Who is this Data Engineer Career Path For?

Our data engineer career path starts with the fundamentals. There is absolutely no experience necessary to start, and everyone is welcome.

This career path is for individuals ready for an amazing career change, data professionals looking to amplify their skill set for that next promotion, and college students who are interested in becoming job-ready.