Job File: Data Engineer

Data refers to the digital data that customers, consumers and members create. The data engineer is the first to access and maintain the data sets.

Information, videos, photos, comments, questionnaires... Data processing is essential to help the strategy and management of a company. A huge source if it is well exploited, it is obviously linked to artificial intelligence.

THE DATA ENGINEER: PRESENTATION AND MISSIONS

The data engineer, also called data engineer, stands at the very beginning of the data processing chain. She is the first one to approach the mega-data that is still raw. She creates the architecture of the data volumes. She is responsible for guaranteeing their storage, clarity and security before handing them over to the other players in the chain. For example, she seeks to detect erroneous, duplicate, invalid or suspicious information... She detects possible malfunctions. She inspects new sources to collect new data. She links different tools together to create a secure architecture.

To summarize the massive data chain: the data engineer retrieves, secures and clarifies the data, then the data analyst studies them (from the perspective of operational and business issues), and it is the data scientist's turn to apply algorithms to transform them, notably into forecasts.

BUSINESS IMPLICATIONS

The data engineer can tackle any data stream. She is therefore able to work for many sectors of activity, on different themes.

Large groups are looking for this type of profile: banks, laboratories, insurance, real estate, telecommunications, energy...

Sometimes in SMEs, a single function groups together the professions of data engineer, data analyst and data scientist.

ETHICAL IMPLICATIONS

The presence of data also implies the notions of confidentiality and freedom. The data engineer is familiar with these issues and can also rely on data and AI lawyers and ethics officers to assist him on specific questions.

Aivancity programs integrate into their learning all the components of artificial intelligence and its challenges, whether technical, technological, commercial, ethical or legal. These are global and hybrid training courses that allow future engineers to benefit from a maximum level of knowledge and a wide know-how.

KEY COMPETENCIES

The data engineer develops data flows. She is familiar with programming languages (Javascript, Scala and Python...), database tools (SQL and NoSQL), systems that manage data such as Hadoop. Her job is to prepare the ground to make the further processing more fluid.

The data engineer works in a team, good people skills are therefore imperative. Accuracy and analytical skills are among her main qualities. She is organized, rigorous and synthetic.