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.

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: AWS Kinesis, Data Engineering, Amazon Redshift, Apache Kafka, Cloud Computing Architecture, Data Lakes, Real Time Data, Amazon Elastic Compute Cloud, Data Management, Apache Hive, Data Visualization Software, Cloud Storage, Amazon S3, Data Integration, Data Architecture, Data Migration, Performance Tuning, Serverless Computing, Database Architecture and Administration, AWS Identity and Access Management (IAM)
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: Data Engineering, Data Pipelines, Data Transformation, Extract, Transform, Load, Data Integration, Data Warehousing, Software Development Tools, Data Import/Export, Stored Procedure, SQL, Data Analysis, GitHub, Microsoft Visual Studio, Command-Line Interface
Intermediate · Course · 1 - 3 Months

Snowflake
Skills you'll gain: Data Engineering, Database Management, Databases, Data Pipelines, Change Control, DevOps, CI/CD, Command-Line Interface, Version Control, System Monitoring, Continuous Monitoring, Data Analysis
Advanced · Course · 1 - 4 Weeks
Starweaver
Skills you'll gain: Retrieval-Augmented Generation, Vector Databases, AI Personalization, Data Engineering, System Monitoring, Generative AI, Prompt Engineering, Data Processing, AI Workflows, Scalability, Data Architecture, Data Pipelines, Embeddings, Performance Tuning, Continuous Monitoring, Database Systems, Talent Pipelining, Process Optimization, Engineering
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Data Engineering, Data Warehousing, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, SQL, Database Administration, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Store, Generative AI, Data Import/Export, Data Security
Intermediate · Professional Certificate · 3 - 6 Months

Skills you'll gain: Azure Synapse Analytics, Performance Tuning, Microsoft Azure, System Monitoring, Data Engineering, Transact-SQL, Star Schema, Power BI, PySpark, Data Cleansing, Data Analysis Expressions (DAX), Apache Spark, Data Warehousing, Analytics, Data Modeling, Data Analysis, SQL, Azure Active Directory, Advanced Analytics, Microsoft Copilot
Intermediate · Specialization · 1 - 3 Months

Skills you'll gain: Data Storytelling, Data Engineering, Data Presentation, Key Performance Indicators (KPIs), Dashboard, Business Analytics, Business Intelligence, Extract, Transform, Load, Data Transformation, SQL, Automation, Data Management, Version Control
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Data Engineering, Data Manipulation, Data Warehousing, Cloud Development, SQL, Data Pipelines, Extract, Transform, Load, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Role-Based Access Control (RBAC), Stored Procedure, Data Storage, Database Management, Generative AI, Data Science, Data Import/Export, Machine Learning
Beginner · Course · 1 - 4 Weeks

Snowflake
Skills you'll gain: Prompt Engineering, Retrieval-Augmented Generation, Generative AI, LLM Application, Data Engineering, Data Manipulation, Snowflake Schema, Large Language Modeling, Model Deployment, Data Warehousing, Unstructured Data, Embeddings, Cloud Development, SQL, Natural Language Processing, Data Pipelines, Extract, Transform, Load, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Role-Based Access Control (RBAC)
Beginner · Professional Certificate · 1 - 3 Months

LearnQuest
Skills you'll gain: AI Workflows, Technical Communication, AI Enablement, Model Deployment, Generative AI Agents, Data Integration, AI Orchestration, Reinforcement Learning, Artificial Intelligence and Machine Learning (AI/ML), Agentic systems, Responsible AI, Artificial Intelligence, Cloud Computing, Deep Learning, Data Visualization, Python Programming, Machine Learning, Data Engineering, Anomaly Detection, Statistical Analysis
Beginner · Specialization · 1 - 3 Months

Amazon Web Services
Skills you'll gain: Data Lakes, Data Visualization, Data Architecture, Amazon Web Services, Data Engineering, Data Infrastructure, Data Warehousing, Data Processing, Amazon S3, Query Languages, AWS Identity and Access Management (IAM), Data Management, Data Transformation, Data Governance, Data Import/Export, Data Storage, Data Science, Machine Learning
Beginner · Course · 1 - 3 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.‎