In today’s world, data plays a crucial part in the decision making process. The world completely runs on data, and not a single organization can think of processing without a data-driven strategic plan. The amount of data we produce every day would amaze you. There are around 2.5 quintillion bytes of data created every day at the current pace, but the pace is accelerating. As Big Data and analytics have emerged as a lucrative career path, there has been an ongoing discussion about the difference between several data science roles and responsibilities because of its invaluable insights.
In this article, I will take you through the key differences and similarities between a Data Engineer and Data Scientist. Let’s have a look at what is covered in this article:
- Who is a Data Engineer, Data Scientist?
- Skills Required
- Roles and responsibilities
- Salary and Job trends
Before we proceed, it is essential to have an insight that there is a significant overlap when it comes to skills, roles, and responsibilities, and the salary offered between Data Engineers and Data Scientists.
Who is a Data Engineer?
A Data Engineer is a data professional who works to support the analyst and Data Scientists by providing tools and infrastructure that can be used to deliver end-to-end solutions to several business problems. Data engineers are involved in preparing data; they develop, construct, test, and maintain the complete architecture.
Who is a Data Scientist?
A Data Scientist is a data professional who analyses and interprets large sets of structured and unstructured data. Data Scientists are Big Data wranglers having in-depth knowledge of computer science, statistics, and mathematics. They are analytical experts utilizing their skills and expertise in both technologies and social science to find trends and manage data. Their work actually revolves around data and bringing out a sense from unstructured data from several sources such as social media feeds, emails, and smart devices.
Having knowledge of programming languages and coding skills are the must-have skills for Data Engineers and Data Scientists.
|Data Engineer||Data Scientist|
|Data Warehousing & ETL||Data Mining|
|Big Data frameworks (Hadoop, MapReduce, Pig, Hive, Apache Spark)||Machine Learning and Deep Learning principles|
|In-depth knowledge of SQL||Big Data frameworks (Hadoop, Pig, Apache Spark)|
|Data Architecture and pipelining||Data Optimization|
|Machine Learning principles||Decision making|
|Scripting, reporting, and Data visualization||In-depth programming knowledge (R, SAS, Python, Java)|
Roles and Responsibilities
The roles and responsibilities of a Data Engineer and Data Scientists are quite similar as you would have understood by the skills mentioned above.
- A Data Engineer is responsible for developing, constructing, testing, and maintaining data architectures such as databases and large-scale processing systems.
- Data engineers validate the raw Data that contains human and machine errors.
- They recommend and implement ways to improve data quality, reliability, and efficiency.
- They develop a data set process for data mining, modeling, and production.
- They need to deploy machine learning and statistical models.
- They build pipelines for various ETL operations.
- A Data Scientist is responsible for managing, mining, and cleaning structured and unstructured data to prepare it for actual use and processing.
- They develop models that can operate on Big Data.
- They need to interpret and understand Big Data analysis.
- They employ analytics programs, machine learning, and statistical methods to prepare data for use in prescriptive and predictive modeling.
- They explore and examine data to find hidden patterns.
- They need to research to answer industry and business questions.
Salary and Job Trends
The demand for Data Engineers and Data Scientists has rapidly grown in the fast few years. Nowadays, every company in every industry requires Data specialists to manage and manipulate data.
According to Glassdoor, there are 69735 jobs available for Data Engineers in the United States and around 10107 jobs available in India till date. As the job requires a piece of extensive knowledge and experience, the salary offered to the Data Engineers is attractive. As per 2,479 salaries submitted on Glassdoor reveals the average salary of a Data Engineer in the United States is $103K per year, and Rs. 8,36,000 per year in India.
Talking about Data Scientists, there are 21296 jobs available for Data Scientists in the United States and around 1600 jobs in India to date. The average salary offered to a Data Scientist in the United States is $113K per year and Rs. 10,15,000 per year in India.
Now that you have come across the difference between Data Engineer and Data Scientist, their skills, roles, and responsibilities, jobs, and salaries offered. It is time to take a step ahead, regardless of the career path you decide to pursue, it will be essential to equip yourself with some advanced degree or certifications. A Data Engineering course will make you proficient in the tools and systems used by Data Science professionals, wherein you can master the Big Data and Hadoop frameworks.
Author | Emily Forbes
An Entrepreneur, Mother & A passionate tech writer in the technology industry!