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4 Data Engineer Certifications: Which One Is Right For You?
Written by Coursera • Updated on
Whether you are already a data engineer, hoping to switch careers, or just getting started, earning a data engineer certification can help you achieve your professional goals.
Data is one of the world’s most valuable resources. According to the World Economic Forum, the world’s data was worth around $3 trillion in 2017, a number that has surely grown in the past five years [1]. Data engineers are responsible for designing and building the systems for collecting, storing, and analyzing big data that is applicable to nearly every industry.
Many of those hoping to break into or enhance their data engineering career often wonder whether they need a certification—and if so, which one suits their career objectives.
In this article, we’ll guide you through whether you need a data engineer certification or not and answer the question, “Which data engineer certification is right for me?”
Do you need a data engineer certification?
Before we answer whether you need one, what is a data engineer certification?
Certification vs. certificate
Certifications and certificates sound similar, but they are not quite the same. A certificate is proof that an individual completed a professional training course. A certification is proof that an individual took and passed a specific exam. Many certificates do allow you to take an exam upon completion that can result in a certification.
If you are an early-career professional, you can learn data engineering skills and tools like Google Cloud or Azure in a standardized, comprehensive, and chronological manner. If you are an established data engineer, you can fill in the gaps in your skills, knowledge base or stay up-to-date on the latest tools and technologies.
Either way, you can display the certification credential on your LinkedIn profile for added visibility and proof of your data engineering skills.
Is a certification worth it?
Certifications and professional certificates can help aspiring data engineers enter the field or boost their prospects.
For example, the Google Cloud Data Engineer Professional Certificate was ranked #1 on Global Knowledge’s list of 15 top-paying certifications in 2021 [2]. This certificate program is one that is linked to a certification exam.
Further, in a 2021 survey of program graduates, 75 percent of Google certificate graduates in the US reported an improvement in their career trajectory within six months of completion [3]. Similarly, research conducted by the US Bureau of Labor Statistics in 2020 found that professionals with either a certification or license earned more on average than those without either and faced lower levels of unemployment [4].
Still, a certification can be an investment of time and money, so it’s important to make a choice that suits your current career goals.
4 popular data engineer certifications
There are plenty of certification and certificate programs available for aspiring and established data engineers. Here’s a list of popular certifications that Coursera offers, so you can choose the option that best suits your career goals.
The cost for each of the professional certificate programs below is $40 per month with Coursera Plus.
1. IBM Data Engineering Professional Certificate
IBM’s Data Engineering Professional Certificate is a flexible online certificate program that provides learners with job-ready skills, tools, and a portfolio in 15 months or less (based on 4 hours per week). The course is designed to prime you for an entry-level data engineer position. You’ll learn how to use Python to extract, transform, and load (ETL) data, work with relational databases, query data using SQL, and work with big data engines Hadoop and Spark.
You can earn up to 12 college credits upon completing this program.
Requirements: This program does not require any prior data engineering or programming experience, or any specific educational background.
professional certificate
IBM Data Engineering
Launch your new career in Data Engineering. Master SQL, RDBMS, ETL, Data Warehousing, NoSQL, Big Data and Spark with hands-on job-ready skills.
4.6
(2,685 ratings)
35,069 already enrolled
BEGINNER level
Learn More
Average time: 5 month(s)
Learn at your own pace
Skills you'll build:
Relational Database Management Syste (RDBMS), ETL & Data Pipelines, NoSQL and Big Data, Apache Spark, SQL, Data Science, Database (DBMS), NoSQL, Python Programming, Data Analysis, Pandas, Numpy, Information Engineering, Jupyter notebooks, Web Scraping, Extract Transform Load (ETL), Database (DB) Design, Database Architecture, Postgresql, MySQL, Relational Database Management System (RDBMS), Cloud Databases, Shell Script, Bash (Unix Shell), Linux, Database Servers, Relational Database, Database Security, database administration, Extraction, Transformation And Loading (ETL), Apache Kafka, Apache Airflow, Data Pipelines, Data Warehousing, Cube and Rollup, Business Intelligence (BI), Star and Snowflake Schema, cognos analytics, Mongodb, Cloud Database, Cloudant, Cassandra, Apache Hadoop, SparkSQL, SparkML, Big Data, Relational Databases
2. Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate
Google’s Cloud Data Engineer Professional Certificate is a flexible online certificate program that provides you with a strong foundation in key big data and machine learning products in Google Cloud in five months or less. It incorporates hands-on labs using Qwiklabs. Designed for professionals with a base level understanding of data engineering concepts, this certificate program is meant to prepare you for the Google Cloud Certification. Keep in mind that not all companies use Google Cloud, so this is not a certification exam that qualifies you as a data engineer, but rather for data engineering on Google Cloud only.
This is a popular option for a professional certificate in data engineering. According to a 2020 Gallup survey, 81 percent of certificate graduates felt they could prove cloud skill competency to recruiters and 85 percent felt more confident in cloud skills [5].
Requirements: This professional certificate is intended for intermediate level data engineers, so you should have basic proficiency with SQL and experience developing applications using common programming languages.
Cost: The registration fee for the Google Cloud Professional Data Engineer Certification is $200.
professional certificate
Preparing for Google Cloud Certification: Cloud Data Engineer
Advance your career in data engineering
4.6
(6,619 ratings)
74,816 already enrolled
INTERMEDIATE level
Learn More
Average time: 5 month(s)
Learn at your own pace
Skills you'll build:
Information Engineering, Google Cloud, Bigquery, Tensorflow, Cloud Computing, Google Cloud Platform
3. IBM Data Warehouse Engineer Professional Certificate
IBM’s Data Warehouse Engineering Professional Certificate is a flexible online certificate program that provides learners with job-ready skills, tools, and a portfolio in eight months or less. Designed for data warehouse engineer beginners, you’ll acquire the essential skills needed to work with a range of tools and databases to design, deploy, and manage enterprise data warehouses, such as building data pipelines with Apache Airflow and Kafka to ETL data.
Requirements: This program does not require any prior data engineering or programming experience, or any specific educational background.
professional certificate
IBM Data Warehouse Engineer
Kickstart your Career in BI Engineering. Develop job-ready skills for an entry level role in Data Warehousing.
4.7
(293 ratings)
4,345 already enrolled
BEGINNER level
Learn More
Average time: 3 month(s)
Learn at your own pace
Skills you'll build:
Relational Database (RDBMS), Business Intelligence (BI), Enterprise Data Warehouse (EDW), SQL, Extract Transform Load (ETL), Data Science, Database (DBMS), NoSQL, Database (DB) Design, Database Architecture, Postgresql, MySQL, Relational Database Management System (RDBMS), Cloud Databases, Python Programming, Jupyter notebooks, Shell Script, Bash (Unix Shell), Linux, Database Servers, Relational Database, Database Security, database administration, Extraction, Transformation And Loading (ETL), Apache Kafka, Apache Airflow, Data Pipelines, Data Warehousing, Cube and Rollup, Star and Snowflake Schema, cognos analytics
4. Meta Database Engineer Professional Certificate
Meta’s Database Engineer Professional Certificate is a flexible online certificate program that prepares learners for entry-level database engineering roles in six months or less. Designed for beginners, you’ll learn the key skills required to create, manage, and manipulate databases, along with programming languages and software such as SQL, Python, and Django.
Requirements: This program does not require any prior data engineering or programming experience, or any specific educational background.
professional certificate
Meta Database Engineer
Launch your career as a Database Engineer. Build job-ready skills for an in-demand career and earn a credential from Meta. No degree or experience required to get started.
4.6
(666 ratings)
19,022 already enrolled
BEGINNER level
Learn More
Average time: 6 month(s)
Learn at your own pace
Skills you'll build:
SQL and Python syntax, database management, database administration, MySQL, Tabular records, Database (DBMS), Linux, Web Development, Bash (Unix Shell), Github, Version Control, Data Management, Relational Database, Database (DB) Design, Cloud Hosting, Application Programming Interfaces (API), Python Programming, Computer Programming, Django (Web Framework), Data Model, Extraction, Transformation And Loading (ETL), Data Warehousing, Application development, Project Management, Pseudocode, Algorithms, Communication, Data Structure, Computer Science
Enhance your data engineer career today
Data engineering is a popular, in-demand career field that can be exciting and fulfilling. If you enjoy building and tinkering with data systems to support business goals, you might be interested in one of the four Coursera professional certificates above.
Written by Coursera • Updated on
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.