Introduction to Big Data and Data Professionals
Big data is changing the way we do business and creating a need for Data Engineers who can collect and manage large quantities of data.
Data Engineers are in demand in the UK and are becoming more expensive. According to Glassdoor, Data Engineers have an average salary of £49,514 per year in the United Kingdom, with contractors going for much more.
The Data Engineer
The Data Engineer’s primary role is to prepare data for analytical or operational uses. They are the data pipeline builders who bring together information from various sources. The data is integrated, consolidated and cleansed for use in analytics applications.
Depending on the size of an organisation, the Data Engineer will work with a different scale and complexity of data. The larger the organisation, the more complicated the analytics architecture and the more data it will be responsible for.
Data Engineers work in data teams with Database Administrators and Data Analysts to improve data transparency and enable businesses to make more responsible business decisions.
Data Engineering Skills
The basics include cloud computing fundamentals, coding skills, and database design. Data Engineers, however, should be proficient in the following:
- ETL, which stands for extract, transform, and load, is the process data engineers use to extract data from different sources, transform the data into a usable and trusted resource, and gear that data into the systems end-users can access and use downstream to solve business problems. ETL tools include Xplenty, Stitch, Alooma, and Talend.
- Data is most commonly stored in databases, so a thorough understanding of relational and non-relational databases is essential.
- Languages such as SQL, NoSQL, Python, Java, R, and Scala. Data Engineers need to be confident and efficient coders.
- Many types of data storage exist, from data lakes to data warehouses. Data Engineers must understand the various types of data storage available and when and where to use them.
- Repetitive tasks call for automation; in big data, a lot can and should be automated.
- Data Engineers can be responsible for extensive data management, so skills in technologies like Hadoop, MongoDB, and Kafka are beneficial.
- Data security is an area that all data professionals should be experts in, even if the organisation they are working with have their own dedicated data security teams. Data needs to be protected at all times.
Hopefully, this article has helped clarify what a Data Engineer is and what they do.
To stay competitive, organisations need to leverage data whenever and wherever possible to enhance business effectiveness and efficiency.
To create such an environment, organisations need to create and develop data teams and understand who the key role-players are that contribute to their organisation being data-driven.