OVERVIEW
Gain the In-Demand Data Engineering Skills Needed to Power the Future of Analytics
As organizations continue to embrace data-driven strategies, data engineering has emerged as a critical and rapidly growing discipline. Businesses in every industry—from technology and finance to healthcare and retail—require skilled professionals who can build and manage scalable data infrastructures, optimize cloud databases, and support real-time analytics. The rise of AI adds to the need for data engineers as employers seek to prepare and manage large data sets for AI-driven models.
The Data Engineering Professional Certificate equips professionals with the essential technical competencies to process, store, and analyze massive datasets across cloud environments. This program is designed for those with a background in data analytics, cloud computing, or IT who want to expand their expertise and advance their career in data engineering.
Through this program, you will develop expertise in:
- Cloud Databases—Design, develop, and deploy distributed databases using three cloud platforms: Amazon AWS, Microsoft Azure, and Google Cloud Platform.
- Data Processing – Build and optimize data pipelines for large-scale analytics using technologies like Apache Airflow and AWS Redshift.
- Big Data Analytics – Process and analyze massive datasets, comparing cloud environments to determine the best approach for various business needs.
- Enterprise-Scale Data Engineering – Work with real-world datasets, develop automated data workflows, and ensure compliance with governance and security best practices.
This hands-on, self-paced certificate focuses on real-world applications, ensuring that graduates are job-ready with the ability to work across multiple cloud environments and data platforms.
Time to complete certificate
7 months
Learners should plan to dedicate 15–20 hours per week to the program.
Cost
$3,500
Tuition covers costs for any e-textbooks or other resources.
Certificate consists of
3 courses
This certificate has 3 courses and transferable competency units toward a WGU degree program.
COURSES
Data Engineering Professional Courses
WGU is known for the high return on investment of its degree programs. This certificate is no exception. Industry data, employers, and student feedback are used to ensure that all courses remain relevant and effective. WGU Certificates are designed with your future in mind.
The certificate is a self-directed, competency-based program you can complete on your own schedule. We recommend dedicating 15–20 hours per week for seven months to complete the program successfully.
The 3 courses in this program are:
In this course you will:
- gain knowledge on the application of cloud architectures to large-scale data systems.
- learn the differences between cloud-native approaches to data architectures and smaller-scale systems.
- apply cloud computing concepts to address specific business scenarios.
In this course you will:
- apply the practice of automating data flow into and out of components of an analytics system.
- transform data to elevate quality in alignment with requirements for extract, transform, and load (ETL) pipeline operations on data at scale and variations of ETL as a function of data repositories, including data warehouses and data lakes.
- stream and batch data operations and implement pipeline solutions in cloud-native environments.
In this course you will:
- uncover approaches for analyzing large data sets.
- learn map/reduce approaches, Apache Spark, and cloud–native solutions for developing, automating, and scaling data analytics.
- learn methods for integrating data processing pipelines and data stores to create comprehensive data analytics architectures.
WGU CERTIFICATES POWERED BY WGU ACADEMY
Why Choose a Certificate?
If you're not quite ready to commit to a full degree program, want to try out online learning, or need a faster way to boost your résumé, a WGU certificate could be the right fit for you. With a certificate program, you can begin any time you want—no need to wait for the first of the month. WGU Certificates are also self-paced, so you can move as quickly as you are able to master the material. Plus, the certificate courses are transferrable to WGU degree programs, so you can continue your education whenever you're ready.
100% Online Courses that Work with Your Schedule
Our certificates are 100% online, and there are no set class times. This means you can work on your certificate whenever it makes sense for you and your busy schedule. You're in the driver's seat of your education.
Full Suite of Support Services
WGU has deep experience serving learners from a wide range of professional and academic backgrounds. Our instruction, coaching, and career resources will help you complete your certificate and reach your goals.
Competitive Pricing
Our certificate is $3,500 for a 7-month total program. With a cost that is extremely competitive for similar programs, you'll find that WGU certificates are an excellent match for your needs.
COST
An Affordable Certificate
The purchase price enrolls you in the program for the term length shown, which is the average time it takes most learners to complete all courses in the program. If you do not complete your program by the last day of the term, your enrollment will automatically change to a $499 monthly subscription. The credit card you provide will be charged at that time, allowing you additional time to complete your program. You may cancel at any time.
$3,500
Total cost
For this certificate, there are no additional fees.
HOW IT WORKS
Here's What You Can Expect from This Certificate
- Designed for professionals – Ideal for those with a background in data analytics, IT, cloud computing, or software development.
- Flexible, self-paced learning – The program follows WGU’s competency-based model, allowing you to progress as soon as you demonstrate mastery.
- Transferable credits – This certificate provides credit toward a WGU degree program.
- Real-world case studies – Learn by working with industry-standard tools like Apache Airflow, AWS Redshift, Google Cloud Spanner, and AWS DynamoDB.
- Project-based learning – Complete hands-on projects that simulate real-world data engineering challenges.
ADMISSIONS
Admission Recommendations
To successfully complete this certificate program, you should:
1. Possess a bachelor’s degree in a STEM field
OR
2. Possess any bachelor’s degree plus ONE of the following:
- Completed college-level coursework in statistics and computer programming with a grade of B- or better. Students may complete the Foundations of Coding and Applied Probability and Statistics courses at WGU Academy prior to enrolling in the program.
- At least two years of work experience in a data analytics, data science, data engineering, or database administration role
- A current and active third-party certification in data analytics, data science, or data engineering from this list:
- CompTIA Data+
- DASCA Associate Big Data Engineer
- DASCA Senior Big Data Engineer
- Udacity Data Analyst Nanodegree
- Udacity Data Scientist Nanodegree
- Udacity Data Engineering with AWS Nanodegree
- Associate Certified Analytics Professional (aCAP)
- Certified Analytics Professional (CAP)
- Cloudera Data Platform (CDP) Data Analyst
- Microsoft Certified: Azure Data Scientist Associate
- SAS Certified Advanced Analytics Professional
- WGU Data Skills Certificate
CAREER OUTCOMES
Unlock Career Opportunities in a High-Growth Field
Data engineering is one of the fastest-growing tech jobs, with 57,000+ job openings in the past year alone and 30%+ projected growth through 2033. Employers across industries seek professionals with the skills to build, optimize, and manage large-scale data platforms.
Industries Where Data Engineering Skills Are in Demand:
- Technology & IT Services – Developing and maintaining high-performance cloud-based data infrastructure.
- Healthcare – Managing large datasets for patient care insights, predictive analytics, and AI-driven diagnostics.
- Financial Services – Creating secure, scalable data environments for fraud detection and financial modeling.
- Retail & E-Commerce – Optimizing customer data pipelines and recommendation engines.
- Manufacturing – Powering IoT-enabled predictive maintenance and supply chain analytics.
Ready to Start?
