Data Engineering Certification

Top Data Engineer Certification Programs

Data. It’s everywhere. And with that, comes a ton of questions. How can I make it easier to use? What is the right way to structure it? How do I collect and manage it? These are just some of the things a data engineer needs to ask moving forward with a data extract, transform, and load (ETL) strategy.

Fortunately, with the rise of data engineering as a career path, there are more opportunities than ever to become a world-class data engineer. If you’re just starting your career as a data engineer or planning to advance in your role, then earning a data engineer certification may help you gain credibility within the company.

Our Top 10 Picks

Udacity Logo
Data Engineer Nanodegree
Best all-around data engineer certification
Dataquest
Professional Certificate in Data Engineering
Best professional certification
Dataquest
Data Engineer Career Path
Best beginner data engineer courses
Udacity Logo
Data Engineering with Microsoft Azure
Best project-based data engineer certification
IBM
Professional Certificate in Data Engineering Fundamentals
Best for beginners
DataCamp
Data Engineer With Python Career Path
Best Python data engineer courses
Duke University
Python, Bash, and SQL Essentials for Data Engineering Specialization
Best mid-range data engineer program
IBM
Professional Certificate in Data Warehouse Engineering
Best for data warehousing
Udacity Logo
Data Scientist Nanodegree
Best data engineer program for experienced users
Google Square
Data Engineering, Big Data, and Machine Learning on GCP Specialization
Best alternative data engineer program

1. Data Engineer Nanodegree (Udacity)

Udacity Logo

Get the skills you need to build production-ready data infrastructure. The online 5-month Udacity Data Engineer Nanodegree program will help you learn about what it takes to become a data engineer.

Get the skills you need to design, build, and operate data-driven systems. This program covers all the essential skills of data engineers including data modeling, data warehouses, data lakes, and data pipelines. In the capstone project, you’ll gather, wrangle, and combine data sources into a clean database for analysis.

Courses

  1. Data Modeling – Get your skills in data modeling and relational design to fit your specific needs. Use this course to learn how to build data models that fit the needs of data consumers. At the end of this course, you’ll gain foundational skills in ETL, data modeling, and Apache Cassandra.
  2. Cloud Data Warehouses – Get a deeper understanding of data infrastructure and how to create cloud-based data warehouses on AWS. In this course, you will gain the skills and knowledge you need to create and manage cloud-based data warehouses on AWS.
  3. Spark and Data Lakes – Get started with data analytics and Spark today. This course will teach you how to store, query, and use big data in a Spark environment.
  4. Data Pipelines with Airflow – Take control of your data pipelines and ensure quality and performance. This course will teach you how to schedule, automate, and monitor data pipelines using Apache Airflow.
  5. Capstone Project – This project will give you the skills and knowledge you need to build an effective data engineering portfolio project. You will get the skills you need to gather, transform, and clean data using the ETL process for others to analyze.

Skills Acquired

  • Data Modeling
  • Extract, Transform, Load (ETL)
  • Cloud Data Warehouses
  • NoSQL Data Models
  • Relational Databases
  • PostgreSQL
  • Apache Cassandra
  • Data Warehouses and Lakes
  • S3 and Redshift
  • Apache Spark
  • Big Data
  • Data Engineering
  • Airflow

For more information, read our review of the Udacity Data Engineer Nanodegree.

  • PREREQUISITES: This program requires intermediate Python and SQL.

2. Professional Certificate in Data Engineering (IBM)

IBM

Learn how to design data engineering systems in the Professional Certificate in Data Engineering. As an aspiring data engineer, you will learn how to design and build data pipelines, data stores, and ETL tools.

Get the skills you need to design data pipelines including tools such as Apache Airflow and Apache Kafka. By the end of this 14-course program, you will be able to populate data warehouses and use Business Intelligence (BI) tools like Cognos Analytics.

**See #5 if you’re interested in the shortened version with 6 skill-building courses from IBM.

Courses

  1. Data Engineering Basics for Everyone – Learn about the basic concepts of data engineering so that you can start building ETL processes today. This course is designed for people who want to work in data engineering and learn about its lifecycle.
  2. Python Basics for Data Science – This course provides a beginner-friendly introduction to Python with coding practice and script-building techniques.
  3. Python for Data Engineering Project – Learn the basics of Python and data engineering, and apply them to a real-world problem.
  4. Relational Database Basics – Take the first step in learning Relational Database Management Systems (RDBMS) and learn everything from MySQL to PostgreSQL and IBM Db2.
  5. SQL for Data Science – Learn how to use SQL to extract data from databases and use it to build smarter insights.
  6. SQL Concepts for Data Engineers – Acquaint yourself with SQL so you can design more efficient and effective data analysis and manipulation.
  7. Linux Commands & Shell Scripting – Get up to speed with Linux Shell Commands and shell scripting basics.
  8. Relational Database Administration (DBA) – Get the skills you need to be a DBA for any database, including MySQL, PostgreSQL, and Db2. By the end of this course, you will have the skills you need to take on the relational database administrator role.
  9. Building ETL and Data Pipelines with Bash, Airflow and Kafka – You will learn how to build ETL and data pipelines using shell scripts, Airflow and Kafka. You will also learn how to use these tools to automate data processing tasks.
  10. Data Warehousing and BI Analytics – Get trained in how to design, implement, and analyze a data warehouse and BI system. Learn how to use SQL and BI tools to get the most out of your data.
  11. NoSQL Database Basics – Get started with the basics of NoSQL databases. You’ll learn the four key non-relational database categories and how to work with them.
  12. Big Data, Hadoop, and Spark Basics – Enhance your Big Data skills with this comprehensive course that provides foundational knowledge and analytical skills. Learn and practice your Big Data skills hands-on with Hadoop and Spark.
  13. Apache Spark for Data Engineering and Machine Learning – Take the first steps in learning how to use Apache Spark to power your data infrastructure. This course teaches you the basics of Spark Structured Streaming, ETL for Machine Learning (ML) Pipelines, and Spark ML.
  14. Data Engineering Capstone Project – This Capstone Project will give you a deep understanding of the skills and knowledge required to implement, analyze, and manage data in a modern system that includes ETL, Big Data, data warehousing, and BI tools.

Skills Acquired

  • Data Engineering
  • Python
  • Cloud Data Warehouses
  • Relational Database Management (RDBMS)
  • MySQL
  • PostgreSQL
  • IBM Db2
  • SQL
  • Bash
  • Linux Shell Commands
  • Database Administrator (DBA)
  • Extract, Transform, Load (ETL)
  • Airflow
  • Kafka
  • Business Intelligence (BI)
  • NoSQL
  • MongoDB
  • Cassandra
  • IBM Cloudant
  • Big Data
  • Hadoop
  • Apache Spark
  • Machine Learning (ML) Pipelines
  • Spark Structured Streaming
  • Cognos Analytics
  • Snowflake
  • Data Lakes + Warehouses
  • SparkSQL
  • INFORMATION: This program contains 14 skill-building courses and takes approximately 1 and 2 months to complete.

3. Data Engineer Career Path (Dataquest)

Dataquest

Get the skills you need to work with data architectures, manage data pipelines, and maintain data systems. In the Data Engineer Career Path, you will learn about the different aspects of data engineering and find out how to use them to power your business.

Get a better understanding of how to build data pipelines, process data, and extract insights from large data sets. This 7-course career path from Dataquest will help you develop your skills as a data engineer, and give you the knowledge and tools you need to tackle any data problem.

Courses

  1. Introduction to Python – Get started with Python and learn programming concepts for data engineering. This course will teach you the basics of Python and give you the tools to build powerful scripts with a focus on data engineering.
  2. Introduction to Algorithm – Get a better understanding of the time and space complexity of algorithms, so you can make better decisions in your coding and data engineering projects.
  3. Command Line and Git – Get started with version control in Git and learn how to use the most common commands for Bash.
  4. Working with Data Sources – Get started with SQL today and learn the basics of data management. First, you’ll learn how to create, access, and query data. Finally, you’ll learn about data modeling, which will help you create powerful reports and gain insights.
  5. Production Databases – Learn how to optimize your production databases so that you can identify bottlenecks. This course will give you the tools and knowledge you need to take improve your Postgres databases skills.
  6. Handling Large Datasets with Python – Get a handle on parallel processing, MapReduce, Pandas, and NumPy with this concise Python course.
  7. Building a Data Pipeline – Get started with Python data pipelines today, and learn how to build the most effective pipelines for your data engineering needs.

Skills Acquired

  • Data Pipelines
  • Python
  • SQL
  • Pandas + NumPy
  • SQLite
  • MapReduce
  • PostgreSQL
  • Data Architecture
  • Command Line
  • Git
  • Version Control
  • Data Engineering
  • Data Structures
  • Recursion and Trees
  • Parallel Processing
  • INFORMATION: This beginner-friendly program requires approximately 5 months to complete.

4. Data Engineering with Microsoft Azure (Udacity)

Udacity Logo

Get a Data Engineer with Microsoft Azure Nanodegree that will equip you with the skills you need to succeed as a data engineer in the cloud. This nanodegree provides you with the knowledge to build data warehouses, data lakes, and lakehouse architecture.

Learn how to build and orchestrate data pipelines, understand the basics of Azure Data Factory, and get hands-on experience with Azure Synapse Analytics. By the end of this online nanodegree program, you’ll gain the necessary skills you need to build data pipelines in Azure.

Courses

  1. Data Modeling – You will learn NoSQL data models, PostgreSQL, and Apache Cassandra. With this course, you will be able to understand these concepts to create high-quality data models.
  2. Cloud Data Warehouses with Azure – Take the first steps in learning how to build and run cloud-based data warehouses. Learn how to design, develop, and operate data warehouses with Azure. This course is perfect for data professionals who want to increase their knowledge and skills in data warehousing.
  3. Data Lakes and Lakehouse with Spark and Azure Databricks – Learn how to build a data lake on Azure Databricks and use Spark to work with massive datasets.  You will also learn how to build lakehouse architectures on the Azure Databricks platform.
  4. Data Pipelines with Azure – Get started with data engineering in Azure using Azure Data Factory and Azure Synapse Analytics. With this course, you will learn the basics of data pipelines and how to run data transformations, optimize data flows, and orchestrate data pipelines in Microsoft Azure.

Skills Acquired

  • Data Modeling
  • Apache Cassandra
  • Cloud Data Warehouses
  • NoSQL Data Models
  • Relational Databases
  • PostgreSQL
  • Cloud Data Warehouses
  • Microsoft Azure
  • Azure Databricks
  • Apache Spark
  • Azure Synapse Analytics
  • Data Engineering
  • Azure Data Factory
  • Data Pipeline
  • PREREQUISITES: This nanodegree program requires experience with SQL, Python, Azure, and Github

5. Professional Certificate in Data Engineering Fundamentals (IBM)

IBM

Gain the skills you need to work as a data engineer in a professional setting. The Professional Certificate in Data Engineering Fundamentals gives you the skills you need to work with Python, relational databases, ETL, and more.

Get the skills you need to succeed in the data engineering field with 6 skill-building courses and an applied project. This data engineering certificate is designed to teach you the essential skills you need to succeed in the data engineering field.

Courses

  1. Data Engineering Basics for Everyone – Get up to speed with the basics of data engineering so you can start thinking about how to use data for your business. In this course, you will learn about its life cycle and ecosystem. You will also learn about how to collect, process, load, process, query, and manage data for decision-making.
  2. Python Basics for Data Science – Start practicing Python today with this beginner-friendly course. In this course, you will learn how to create your own Python scripts and explore the basics of data science with lab exercises.
  3. Python for Data Engineering Project – Get the skills you need to build scripts with Python. Complete this project and learn how to build powerful Python applications using its libraries.
  4. Relational Database Basics – Get a basic understanding of relational databases and Relational Database Management Systems (RDBMS) so you can start working with MySQL, PostgreSQL, and IBM Db2.
  5. SQL for Data Science – Get started with SQL for Data Science and learn how to extract data from databases in a simple and effective way.
  6. SQL Concepts for Data Engineers – This course will teach you the basics of SQL, including views, stored procedures, transactions and joins.

Skills Acquired

  • Data Engineering
  • Python
  • SQL
  • Pandas + NumPy
  • MySQL
  • PostgreSQL
  • IBM Db2
  • ETL Processes
  • Relational Databases
  • INFORMATION: This program contains 6 skill-building courses and takes approximately 4 months to complete.

6. Data Engineer With Python Career Path (DataCamp)

DataCamp

Get the skills you need to streamline data processing and build a high-performance database. With the Data Engineer with Python Career Path from DataCamp, you will learn how to build data pipelines and use Shell, SQL, and Scala in data engineering processing.

Get a handle on Big Data tools so you can streamline your workflow and optimize performance. With a career track degree in data engineering, you’ll be able to take advantage of the latest big data tools such as AWS Boto, PySpark, Spark SQL, and MongoDB.

Simplified Courses

  1. Data Engineering for Everyone – Take this beginner-friendly course to learn how to use data engineering tools and techniques for data science projects.  Finally, learn how to schedule pipelines with Apache Airflow and optimization with AWS Boto.
  2. Python Programming – Learn core libraries like Numpy, Pandas, and PySpark. Then, familiarize yourself with writing efficient functions and object-oriented programming (OOP) in Python.
  3. Data Processing in Shell – First, get an introduction to Shell to automate tasks.  Next, you will learn command-line techniques to process data and use machine learning.
  4. Bash Scripting – Start working with analytics pipelines in the cloud including functions and automation.
  5. Relational Database Design – Get familiar with using SQL and database design.  You’ll also learn about MongoDB including aggregation pipelines.
  6. PySpark Fundamentals – Learn PySpark including how to clean data and work with Big Data, including resilient distributed dataset (RDD).

Skills Acquired

  • Data Engineering
  • Python
  • Shell
  • SQL
  • Scala
  • Data Pipelines
  • AWS Boto
  • PySpark
  • Spark SQL
  • MongoDB
  • Unit Testing
  • Object-Oriented Programming
  • Airflow
  • Relational Databases
  • Big Data
  • INFORMATION: This career path from DataCamp contains 73 hours of coursework in 19 courses.

7. Python, Bash, and SQL Essentials for Data Engineering Specialization (Duke University)

Duke University

Get a head start on your data engineering skills with the Python, Bash, and SQL Essentials for Data Engineering Specialization from Duke University. This online program is tailored to give you the skills you need to work in data engineering.

For instance, you’ll get the knowledge you need to build powerful web applications and data-driven command-line tools.  By the end of this program, you will have the essential skills to build up your portfolio for a data engineering career.

Courses

  1. Python and Pandas for Data Engineering – Learn how to use Pandas and Python to manipulate and analyze data in a Python environment.
  2. Linux and Bash for Data Engineering – Learn how to use Bash to interact with Linux systems and use its features to perform data engineering tasks. Next, you will get a handle on the different Linux commands and their corresponding options to get the most out of your data engineering workflow.
  3. Scripting with Python and SQL for Data Engineering – Get a better understanding of the basics of Python and SQL for data engineering. This course will teach you how to scrape data from websites to work more effectively with data.
  4. Web Applications and Command-Line Tools for Data Engineering – Get a deep understanding of the power of Jupyter notebooks and Python microservices to help you build models and deploy machine learning tasks.

Skills Acquired

  • Data Engineering
  • Python
  • SQL
  • Pandas + NumPy
  • Bash (Unix Shell)
  • Command Line
  • Web Scraping
  • Visual Studio Code
  • Data Management
  • INFORMATION: This beginner-level program contains 4 skill-building courses and takes approximately 4 months to complete.

8. Professional Certificate in Data Warehouse Engineering (IBM)

IBM

Get Professional Certificate in Data Warehouse Engineering from IBM that will help you build powerful data warehouses and data pipelines.  First, this course provides you with the knowledge and skills you need to maintain relational databases with a focus on SQL.

This 8-course online program will give you the skills and knowledge you need to build ETL and data pipelines with Bash, Airflow, and Kafka.  Finally, learn how to design, build, and operate data warehouses and how to use BI analytics to analyze data and predict outcomes.

Courses

  1. Data Engineering Basics for Everyone – Get started in data engineering with this comprehensive course that covers all the basics you need to know about data. You will learn about data warehousing, data lakes, ETL, data pipelines, and much more.
  2. Relational Database Basics – Learn about relational databases and their fundamental concepts. Next, get started with MySQL, PostgreSQL, and IBM Db2 today.
  3. Introduction to SQL – Get a better understanding of how to extract data from databases using SQL. This course will help you improve your data retrieval skills so that you can make better decisions when it comes to managing your data.
  4. SQL Concepts for Data Engineers – Get up-to-date with SQL and learn how to use it to power your data. This SQL-based course will teach you how to use views, stored procedures, transactions and joins to power your data.
  5. Linux Commands & Shell Scripting – Learn how to use Linux commands to automate database tasks and get more out of your data. This course provides an introduction to bash shell scripting, so you can improve your data automation skills.
  6. Relational Database Administration (DBA) – The course provides an in-depth understanding of the relational database management system (RDBMS) and its capabilities. It covers different aspects of designing, securing, troubleshooting, and automating databases.
  7. Building ETL and Data Pipelines with Bash, Airflow and Kafka – Get a hands-on approach to building ETL and data pipelines with Bash, Airflow, and Kafka. After completing this course, you will be able to develop and manage data pipelines and ETL processes using shell scripts, Airflow and Kafka.
  8. Data Warehousing and BI Analytics – Learn how to design, implement and populate a data warehouse and analyze its data using SQL & BI tools.

Skills Acquired

  • Data Engineering
  • ELT Data Pipelines
  • Linux/UNIX Shell Commands
  • Relational Databases
  • Bash
  • Apache Airflow
  • Kafka
  • IBM Cognos
  • BI Tools
  • MySQL
  • PostgreSQL
  • Data Warehousing
  • INFORMATION: This program contains 8 skill-building courses and takes approximately 9 months to complete.

9. Data Scientist Nanodegree (Udacity)

Udacity Logo

Get the skills you need to get ahead in your data science career with the Data Scientist Nanodegree Program from Udacity. This online program offers the training and skills you need to get started in this exciting field.

During this nanodegree program, you will become more proficient in software and data engineering skills.  Finally, you’ll build your data engineering portfolio with several projects including a recommendation system and a final capstone project.

Courses

  1. Solving Data Science Problems – Get the skills you need to solve data science problems and learn the techniques used by the best data scientists. This course will help you build effective data visualizations and understand complex data so you can communicate with various stakeholders.
  2. Software Engineering for Data Scientists – This course will help you improve your software engineering skills, such as building classes and performing unit tests, to create efficient and reliable code.
  3. Data Engineering for Data Scientists – Learn how to use data to make informed decisions, build models and insights, and deploy solutions to the cloud. Our data engineering course is the perfect way for you to get started in building efficient data pipelines.
  4. Experiment Design and Recommendations – Learn how to explore different design options and analyze their results to see which ones are the best for your business. This course will help you make informed decisions about which experiments to run and how to recommend products to your customers.
  5. Data Science Projects – Build up your data science portfolio with a project that challenges and stimulates your thinking. This open-ended project will become the cornerstone of your CV/resume as you demonstrate your skills as a data scientist.

Skills Acquired

  • Data Science
  • Data Visualizations
  • Software Engineering
  • Unit Testing
  • Building Classes
  • Data Engineering
  • Experiment Design
  • A/B Recommendation Systems
  • IBM Watson Studio
  • Data Pipelines
  • Cloud Solutions
  • PREREQUISITES: This Nanodegree program requires knowledge of Python, SQL & statistics.

10. Data Engineering, Big Data, and Machine Learning on GCP Specialization (Google Cloud)

Google

Get the most out of Big Data and data engineering with the Data Engineering, Big Data, and Machine Learning on GCP Specialization. This online program can help you build batch data pipelines, data warehouses, and data processing solutions.

Get a deep understanding of how your streaming data is behaving and how you can analyze it. Finally, learn about the different ways to build streaming data management systems and machine learning models.

Courses

  1. Google Cloud Big Data and Machine Learning Fundamentals – Get up to speed with all the tools and technologies needed to build big data and machine learning models on Google Cloud. This course provides a comprehensive understanding of how to use these technologies and their benefits.
  2. Modernizing Data Lakes and Data Warehouses with Google Cloud – Learn how to improve your data infrastructure by using Google Cloud technologies. You will explore how to build a data warehouse, a data lake, and a data pipeline.
  3. Building Batch Data Pipelines on Google Cloud – Learn about ETL or ELT paradigms for data pipelines.  Next, you’ll learn about tools such as BigQuery, Cloud Data Fusion, and Qwiklabs for the data engineering process on Google Cloud.
  4. Building Resilient Streaming Analytics Systems on Google Cloud – Learn how to build robust streaming data analytics systems on Google Cloud, using modern data processing technologies.
  5. Smart Analytics, Machine Learning, and AI on GCP – First, you’ll learn how machine learning and analytics can be used to insights from your data. Next, you’ll understand the different ways machine learning can be integrated into your data pipelines.

Skills Acquired

  • Data Engineering
  • Big Data
  • Machine Learning
  • Google Cloud Platform
  • Data-to-AI Lifecycle
  • BigQuery
  • Vertex AI
  • Qwiklabs
  • Data Lakes & Warehouses
  • Batch Data Pipelines
  • Streaming Analytics Systems
  • Cloud Bigtable
  • INFORMATION: This intermediate-level program contains 5 skill-building courses and takes approximately 4 months to complete.

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