This pyramid illustrates well the process necessary to use Data in a company.At the base, Software Developers will be working on the collection of all relevant Data for the Data Engineers.Then, Data Engineers will move and transform this Data into “pipelines” for the Data Scientists.Finally, Data Scientist will analyze, aggregate and optimize the data for the company.Sometimes, Research Scientist, Core Data Scientist and Machine Learning Engineer can optimize the Data even more.This specific process is illustrated in “the Data Science hierarchy of needs” fig.1Looking at fig1, it becomes quite understandable that to manipulate Data in a good way, Data tasks have to be divided and given to specific Data specializations.In a proper manner, Data Engineers should build and design what we call “pipelines”.They usually use programming languages such as Java, Scala, C++ or Python to do that work.Next, it permits Data Scientists to start their work which will be focused on analytics, testing, creating and presenting the Data.2 — Data Engineer — The technical part of data — Design — Build — Arange.Data Engineers are specialized in 3 main data actions: to design, build and arrange Data “pipelines”.They are sort of the Data Architects.Data Engineers often have a computer engineering or science background and system creation skills.“Data pipelines are sequences of processing and analysis steps applied to data for a specific purpose..They have also to be comfortable with creating machine learning and artificial intelligence models.What tasks have a Data Scientist in a company?Work on clean dataFind solutions with the data availableCommunicate analyzes with the teamWork onto solution problem and get someWhat competencies wait from a Data Engineer?Good communication skills.Good analysis.Good hypothesis.Broad knowledge in different techniques in machine learning, data mining, statistics, and big data infrastructures.Be a problem solver.4 — What about job openings and salaries in all that?According to Glassdoor:Data Scientist: $139K / year on averageData Engineer: $151 / year on averageAccording to Glassdoor, the number of job openings for data engineers is almost five times higher than the number of job openings for data scientists..This makes sense as most organizations need more data engineers than data scientists on their team.II- Data Engineer vs Data Scientist: what is the state of the Data job market?1 — Data scientists: A growing sectorData Scientist is a dream work on the paper.A good salaryA challenging job where you have to solve complex problemsHowever, troubles come when data scientist comes to little structures and are willing to do tasks that are not in their specialization.When Data Scientists have to deal with all the Data Hierarchy, it can be painful for them as they have not the programming background of Data Engineers.Sometimes, being a Data Scientist in a company could look like that:As a result, studies show that in 2017, 24.0% of Data Scientists have changed job.For sure, the Data Science job market is a flourishing environment which permits to change for the project employee like the most.However, it also shows that a large amount of Data Scientists try to find a better place on the market.Lastly, Data Scientists must have very good communication and persuasion skills to expose their work to the company.. More details