Data Scientist & Data Engineer: A Brief Introduction
The big data and the need for studying the analysis and trends have led to the introduction of Data Science roles. The two crucial functions that emerged from the Data Science domain are Data Engineers and Data Scientists. Let’s find out more about Data Engineers and Data Scientists.
Difference between Data Scientist and Data Engineer:
Data Engineers and Data Scientist have different job responsibilities, and their roles vary from each other. Data Engineers are into building infrastructure for data generation. The knowledge of statistical analysis, as well as advanced mathematics, is used by Data Scientists to interpret and analyze the generated data. Therefore, Data Engineers role is to build infrastructure and maintain them; whereas, Data scientists interact and work with the infrastructure built by data engineers.
Data scientists research on market and business operation. They identify various trends, and they find correlations to work on the data.
Data engineers provide a complete infrastructure solution to support the data scientists to help them with their work in finding an end to end business solutions. Data engineers have to build high performing infrastructure that allows data scientists to deliver business insights. The infrastructure should facilitate the collection of data, managing data, and providing real-time analysis. Data scientists have experience in working on tools like Hadoop, R, and SPSS, and Data engineers offer their support to work with these tools.
Below are the qualifications or education requirement for a Data Engineer:
- A Data engineer will have a bachelor’s degree in information technology, applied math, computer science, quantitative field, or statistics
- They may also have completed their engineering degrees in IBM Certified Data Engineer or Google’s Professional Data Engineer
- Knowledge of programming languages like Python, Java, C++, and Scala
- Experience in building data infrastructures and warehouses
To be a Data Scientists, below are the qualifications that are required:
- Masters degree or even a Ph.D. in a related quantitative field, computer science, or math
- More than 5-years of experience in analytical roles
- Strong mathematical skills and also analytical skills
- Have extensive experience in the following:
- Working with techniques of Machine learning
- Cloud environment
- Understanding of system integration
The Difference in Remittance:
- The salary of a Data Engineer would depend on the job location, role, and also on the experience. The mean salary is about $141000 annually.
- Similarly, a Data Scientists's compensation package depends on their experience and job location. They earn an average salary of around $137000 annually.
A Data Engineer and Data Scientist have different expertise and functions. Data Engineer is a newer role originating from the Data Scientist role. The new role emerged with the need for professionals to focus on preparing data for analysis and data that is production-ready for the data scientist. Before the inception of the Data Engineering role, the Data Scientist's role comprised of both building the data infrastructure and analyzing the data.
Effective communication is a must for a smooth flow of work. They should have a clear understanding of what is required to avoid any errors, which can lead to a waste of time and effort. A data scientist would want their data pipeline to be ready so that they can work without any interruption. Improper data pipeline can lead to a very uncomfortable situation within the team. Therefore data scientists and data engineers have overlapping functions, and they both have to work with effective co-ordination.
There are a few certification programs that will prepare both Data Scientists and Data Engineers on the programming language. Certification Planner is a global leader in training facilitation and offers structured learning opportunities for both Data Scientists and Data Engineers.
For Data Scientists, CP offers certifications like and. These are the courses aligned with the two most popular programming languages in the domain. For Data Engineers, CP offers certification in and . Both the certifications focussing on Hadoop, a set of open-source software utilities that has emerged as a crucial tool for the Data Engineers.
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