Find out what a data engineer does and how the role differs from that of a data scientist.
Data has transformed the ways organisations work and reach their customers. Indeed, the value of the global big data market is forecast to reach a staggering US$103 billion by 2027.
Data not only empowers organisations with the ability to find better ways of working, but also with deeper insights into who their customers are and what they want. This in turn enables organisations to make more data-informed decisions and significantly boost their success.
Definition of a data engineer
Essentially, data engineers develop and design systems for collecting, storing, and managing data at scale. They develop these systems to enable the analytical and/or operational use of the data by their organisations.
Some of the key aspects of a data engineer’s role include:
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Developing and designing systems that bring together data from various sources
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Making data easily accessible
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Optimising an organisation’s big data ecosystem
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Integrating, consolidating, cleansing, and structuring data for use in various analytics applications
How is a data engineer different from a data scientist?
Although similar, there are some key differences between a data engineer and a data scientist.
Some of these differences are:
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Data engineers build the systems, pipelines and platforms for sourcing and managing data, while data scientists gather and analyse data and utilise tools and techniques such as machine-learning and artificial intelligence (AI) to leverage this data
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Data engineers typically require programming skills and proficiency in programming languages, while data scientists don’t necessarily require these
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Data engineers build data systems to make data more accessible and easier to understand for users, while data scientists create data visualisations to communicate data insights to stakeholders within their organisation
What skills do you need to succeed as a data engineer?
Data engineers play a pivotal role in the success of an organisation – the systems they develop can equip organisations with previously unexplored data insights and opportunities that can significantly improve their success.
In today’s digitised world where data has become king, data engineers can prove to be crucial assets to organisations around the world.
Some of the skills you need to succeed as a data engineer include:
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Programming skills – you need to be able to design, write and iterate code and use a range of coding tools and languages
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Data-modelling skills – you need to be able to create data models and be proficient in data-modelling tools, as well as in comparing different data models
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Analytical skills – you need to be able to analyse data and translate it into valuable insights that help to inform business decisions
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Data innovation skills – you need to be able to find innovative ways to use data to improve the efficiency and effectiveness of an organisation
How can data science training help?
With data becoming so pivotal to the success of many organisations around the world, data roles, including data engineer roles, have surged in popularity and risen sharply in demand in recent years.
Having data science training is a fundamental factor in being able to effectively work with data, and in ensuring a successful career in data roles, such as data engineer roles.
Data science training will equip you with both the technical and non-technical skills and knowledge, as well as the critical and analytical thinking you need to harness the power of data and effectively apply it to address real-world business challenges.
If you’re looking to launch or further your career as a data engineer or data scientist, Southampton Data Science Academy offers flexible online short courses that will empower you with the expert-level knowledge and skills you need to successfully harness the power of data and apply it within your organisation:
