The trade off between Data Engineer Vs Data Scientist

Generally when we are talking about trade off, It's define in business term as "A technique of reducing or forgoing one or more desirable outcomes in exchange for increasing or obtaining other desirable outcomes in order to maximize the total return or effectiveness under given circumstances."

So, this type off trade off comes to the mind of new learner or job seekers, which field they can choose for their future.here I like to share my views about both these field ,others can give their views in comment section as well.

Big Data analytics is the important factor which will join to both these fields.

both positions work on big data. one responsible is by creating the Value from the available data and other create a pipeline to store that data. base skills differentiate both the positions.

Data Scientist should have the knowledge about Core competencies, Advance Mathematics and Statistics, Advance Analytics and Knowledge of Machine Learning and Artificial Intelligence. they will have to interact with the business side. their task to find out data insights by using domain knowledge which will be useful for business decision making. by virtue of they will be a good story teller as well so that CEO & other higher authorities understand those insights with simple way. Data Scientist should have a good knowledge about programming as well expertise in any language ( R studio, Python) their programming skills and logic will be different than normal Programmers as they are dealing with Mathematics & Statistics.

Data Engineer Should have the Knowledge about Core Competencies as above mention as well as Advance Programming,Knowledge of Distributed Storage System and Data Pipeline. they have a programming background. This background is generally in Java, Scala, or Python. A data engineer has advanced programming and system creation skills. Data Engineers gives the software solution around Big data. by using pipeline methods they can bring 10-20 big data technologies together, they are responsible for smart tools selection to solve big data problems. data engineer should have a in depth knowledge of various technologies and framework to enable a company’s business processes with data pipelines.

There are some overlapping skills between them, Analytics is the one but Data Scientist are the good Analyst but at other hand in terms of depth knowledge of programming Data engineers are better than Data Scientists.

Another most important connecting thing between them is a big data. Data Engineer create Big data storage and processing pipeline which will be utilize by Data Scientist with their limited knowledge about programming.

The person should first think about the Data engineering and after they can up skills with Mathematics & statistics, they become a good Data Scientist.

The best way to deal with this to learn Machine Learning Techniques.

The person having good academic mindset and the need to put something in production they are called Machine Learning Engineers.

Now with the business terminology what is the trade off between Data Scientist and Data Engineer? The Answer will get as "Machine learning Engineer" as desirable outcomes in order to maximize the total return or effectiveness under given circumstances.

Thanks for your valuable time.....