Data engineering is experiencing rapid growth, and the demand for skilled data engineers is only going to rise. To stay in demand, it is crucial to possess the right skills. Data engineers are responsible for managing, processing, and transforming raw data into valuable information that businesses can use to make decisions. In this post, we will discuss eight essential skills every data engineer should have and how our Data Engineering Course can help you develop these skills.

1. Programming Skills
   Data engineers must be proficient in various programming languages, including Python, Java, and Scala. In our course, we cover Python Fundamentals, teaching you everything from fundamental data types and variables to object-oriented programming and error handling. You will also get hands-on experience through sprints on Python introductory tasks, file I/O tasks, assorted Python katas, and object-oriented tasks.
   
   
2. Mathematics and Statistics
   A strong foundation in mathematics and statistics is essential for data engineers to analyse and interpret data effectively.
   
   
3. Database Management Systems
   Data engineers must be able to work with database management systems like MySQL and Oracle. Our Data Fundamentals module covers advanced SQL syntax, accessing Postgres databases with Python, data modeling, and common data architecture patterns. You will also participate in sprints focused on SQL syntax, practical modeling tasks, and Python.
   
   
4. Big Data Technologies
   Familiarity with big data technologies like Hadoop and Spark is essential for managing and processing large volumes of data.
   
   
5. Cloud Computing
   Data engineers need to be proficient in cloud computing platforms like Amazon Web Services (AWS) and Microsoft Azure. Our Cloud Operations module covers topics such as deploying Lambda functions, using the AWS command line API, shell scripting, Infrastructure as Code using Terraform, CI/CD with GitHub Actions, and monitoring and alerting with Cloudwatch. You will participate in sprints where you'll deploy a simple API server on EC2, deploy and use AWS voice synthesis and image recognition services, work on shell scripting exercises, and deploy a Lambda function.
   
   
6. Data Visualisation
   Data engineers must be able to visualise data in an easily understandable manner. Our Project phase allows you to work in teams to develop a data platform that ingests, processes, and populates an OLAP data warehouse, which can be queried using a dashboard application to display business-relevant data.
   
   
7. Communication Skills
   Data engineers must be able to communicate their findings to both technical and non-technical audiences. Our course includes a focus on teamwork and collaboration, introducing Agile methodologies, writing user stories, conducting effective stand-up meetings, and utilising Git during the Project phase.
   
   
8. Problem-solving Skills
   Data engineers need to solve problems creatively and efficiently. Throughout the course, you will be exposed to various challenges and practical tasks that encourage problem-solving and critical thinking.
   
   
   In the final Review and Wrap-up week, we discuss project outcomes, code quality, techniques used, and possible enhancements. We also provide short introductions to advanced Data Engineering topics and technologies, such as distributed systems (Hadoop, Spark, Databricks, Beam), ELT (the DBT/Snowflake stack), fundamentals of Machine-Learning Operations, orchestration, and streaming data. Our comprehensive Data Engineering Course is designed to equip you with the essential skills to succeed in this exciting and in-demand field, giving you a strong foundation for a rewarding career in data engineering.