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Data refers to the digital data created by customers, consumers and members.

The data engineer is the first to access and manage the datasets.

Information, videos, photos, comments, questionnaires… Data processing is vital for supporting a company’s strategy and management. An immense resource if properly harnessed, it is, of course, linked to artificial intelligence.

Overview and responsibilities of the data engineer

The data engineer, also known as a data analyst, is at the very start of the data processing chain.

They are the first to work with big data, which is still in its raw form. They design the architecture for these data sets. They are responsible for ensuring the data is stored securely, is clear and accurate, and is protected before passing it on to other stakeholders in the chain. For example, they seek to identify erroneous, duplicate, invalid or suspicious information… They detect any potential malfunctions. They examine new sources to collect fresh data. They link different tools together to create a secure architecture.

To summarise the big data chain: the data engineer retrieves, secures and clarifies the data; the data analyst then analyses it (from an operational and business perspective); and it is then the data scientist’s turn to apply algorithms to transform it into forecasts, amongst other things.

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Business implications

The data engineer can tackle any data stream. They are therefore able to work across a wide range of sectors, on a variety of topics.

Major corporations are looking for this type of profile: banks, pharmaceutical companies, insurance firms, the property sector, telecommunications, energy… Sometimes, in SMEs, a single role combines the responsibilities of a data engineer, data analyst and data scientist

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Ethical implications
The presence of data also raises issues of privacy and freedom. Data engineers are well versed in these topics and can also rely on data and AI lawyers, as well as ethics officers, to assist them with complex issues.
aivancity’s programmes incorporate all aspects of artificial intelligence and its challenges – whether technical, technological, commercial, ethical or legal – into their curriculum. These are comprehensive, blended learning programmes that enable future engineers to acquire the highest possible level of knowledge and a broad range of expertise.

Key skills

The data engineer develops data flows. They are familiar with programming languages (JavaScript, Scala and Python, etc.), database tools (SQL and NoSQL), and data management systems such as Hadoop. Their role is to lay the groundwork to ensure the smooth flow of subsequent processing.

Data engineers work as part of a team, so good interpersonal skills are essential. Precision and an analytical mind are among their key qualities. They are organised, meticulous and able to summarise information clearly.

Trends and factors driving change

There are two possible career paths for an experienced data engineer: working independently or moving into management.

It all starts with the data engineer’s work: ensuring the data is relevant, reliable and usable so that it can reveal its full potential.