Data engineering courses can help you learn data modeling, ETL (extract, transform, load) processes, and data warehousing techniques. You can build skills in data pipeline construction, database management, and ensuring data quality and integrity. Many courses introduce tools like Apache Spark, Hadoop, and SQL, that support processing large datasets and optimizing data workflows. You’ll also explore cloud platforms such as AWS and Azure, which facilitate scalable data solutions and enhance your ability to manage data in various environments.

Skills you'll gain: Data Store, Extract, Transform, Load, Data Architecture, Data Pipelines, Big Data, Data Warehousing, Data Governance, Apache Hadoop, Relational Databases, Apache Spark, Data Lakes, Databases, SQL, NoSQL, Data Security, Data Science
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: NoSQL, Apache Spark, Data Warehousing, Database Design, Database Administration, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Web Scraping, Relational Databases, Linux Commands, SQL, IBM Cognos Analytics, Data Store, Generative AI, Professional Networking, Data Import/Export, Python Programming, Data Analysis, Data Science
Build toward a degree
Beginner · Professional Certificate · 3 - 6 Months

Snowflake
Skills you'll gain: Data Engineering, Data Pipelines, Database Management, Data Manipulation, Databases, Data Transformation, Extract, Transform, Load, Data Warehousing, Change Control, DevOps, Cloud Development, SQL, Data Integration, CI/CD, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Role-Based Access Control (RBAC), Software Development Tools, Stored Procedure, Data Analysis
Beginner · Professional Certificate · 1 - 3 Months

Skills you'll gain: Database Design, Web Scraping, SQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Data Pipelines, Big Data, Databases, Data Warehousing, Data Governance, MySQL, Apache Hadoop, Stored Procedure, Data Import/Export, Programming Principles, Python Programming
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Application Programming Interface (API), Automation, Data Analysis
Beginner · Course · 1 - 3 Months

Amazon Web Services
Skills you'll gain: Infrastructure as Code (IaC), Cloud Engineering, Serverless Computing, CI/CD, Data Infrastructure, Amazon Web Services, Data Architecture, AWS Identity and Access Management (IAM), AWS CloudFormation, Infrastructure Architecture, Security Controls, Cloud Applications, Amazon CloudWatch, Terraform
Beginner · Course · 1 - 4 Weeks
Duke University
Skills you'll gain: Pandas (Python Package), Bash (Scripting Language), Version Control, Jupyter, Linux Commands, Git (Version Control System), Shell Script, Linux, Web Scraping, Linux Administration, Data Manipulation, MySQL, Microservices, AWS SageMaker, SQL, JSON, Cloud Engineering, Python Programming, Big Data, Data Science
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: MySQL, Database Management, Database Administration, Data Warehousing, Linux Commands, Data Integrity, Unit Testing, Algorithms, Software Versioning, Command-Line Interface, Software Visualization, Linux, Pseudocode, Query Languages, Collaborative Software, Django (Web Framework), Database Architecture and Administration, Programming Principles, Computational Thinking, Test Driven Development (TDD)
Beginner · Professional Certificate · 3 - 6 Months

Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI, AI Workflows, Context Management, Decision Making
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: AWS Kinesis, AWS SageMaker, AWS CloudFormation, Data Quality, Docker (Software), Data Pipelines, AWS Identity and Access Management (IAM), Data Security, Database Systems, Databases, Cloud-Native Computing, Version Control, Apache Spark, Cloud Engineering, Apache Airflow, Data Modeling, Cloud Security, Data Storage, Cloud Storage, Data Processing
Beginner · Specialization · 1 - 3 Months

Skills you'll gain: SQL, Relational Databases, Stored Procedure, Databases, Query Languages, Jupyter, Data Manipulation, Data Analysis, Pandas (Python Package), Transaction Processing, Python Programming
Beginner · Course · 1 - 3 Months

Skills you'll gain: Data Warehousing, Database Design, Database Administration, SQL, Extract, Transform, Load, Apache Airflow, Relational Databases, Linux Commands, IBM Cognos Analytics, Database Management, Data Pipelines, Apache Kafka, Bash (Scripting Language), Database Architecture and Administration, Shell Script, Data Store, Data Visualization, IBM DB2, Dashboard, File Management
Beginner · Professional Certificate · 3 - 6 Months
Data engineering is the practice of designing, building, and maintaining the systems and architecture that enable organizations to collect, store, and analyze data effectively. It plays a crucial role in today's data-driven world, where businesses rely on data to make informed decisions, optimize operations, and enhance customer experiences. By ensuring that data is accessible, reliable, and secure, data engineers empower organizations to harness the full potential of their data assets.‎
In the field of data engineering, a variety of job roles are available, including Data Engineer, Data Architect, ETL Developer, and Data Warehouse Engineer. These positions often involve working with large datasets, developing data pipelines, and collaborating with data scientists and analysts to ensure that data is structured and available for analysis. With the growing demand for data professionals, opportunities in this field are expanding across industries such as finance, healthcare, technology, and retail.‎
To pursue a career in data engineering, you should focus on developing a range of technical skills. Key competencies include proficiency in programming languages such as Python and SQL, knowledge of data warehousing solutions, and familiarity with cloud platforms like AWS or Google Cloud. Additionally, understanding data modeling, ETL processes, and big data technologies like Hadoop and Spark can be beneficial. Soft skills such as problem-solving and effective communication are also important for collaborating with cross-functional teams.‎
There are several excellent online courses available for those interested in data engineering. Notable options include the DeepLearning.AI Data Engineering Professional Certificate and the IBM Data Engineering Professional Certificate. These programs provide a comprehensive curriculum that covers essential skills and tools needed in the field, making them great choices for learners at various stages of their careers.‎
Yes. You can start learning data engineering on Coursera for free in two ways:
If you want to keep learning, earn a certificate in data engineering, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
To learn data engineering effectively, start by identifying your current skill level and areas for improvement. Begin with foundational courses that cover programming and database management. Gradually progress to more specialized topics such as data warehousing and cloud technologies. Engage in hands-on projects to apply what you learn, and consider joining online communities or forums to connect with other learners and professionals in the field.‎
Data engineering courses typically cover a range of topics, including data modeling, ETL (Extract, Transform, Load) processes, data warehousing, and big data technologies. You may also explore cloud computing platforms, data pipeline design, and data governance. Courses often include practical exercises and projects to help reinforce your understanding and application of these concepts in real-world scenarios.‎
For training and upskilling employees in data engineering, programs like the IBM Data Warehouse Engineer Professional Certificate and the Snowflake Data Engineering Professional Certificate are excellent choices. These courses are designed to equip professionals with the necessary skills to manage and analyze data effectively, making them suitable for organizations looking to enhance their workforce's capabilities in data engineering.‎