What does a Data Scientist, Data Analyst & Data Engineer Do?

What does a Data Scientist, Data Analyst & Data Engineer Do?

What does a Data Scientist, Data Analyst & Data Engineer Do?

In today’s Big Data environment, data is growing at an exponential rate, creating an ever-increasing demand for technologists and professionals that understand how to collect, manage, analyze, and work with this data. 

Furthermore, being a very forward-thinking incubator that has sponsored startups from all over the world across domains for more than a decade, I believed they provided a representative sample of the market from which to conduct my analysis.

Although the exact definition of these professions varies by firm, there are significant variations between what you might perform each day as a data analyst, data scientist, or data engineer.

Data Analysts Job and Roles

While many data analyst roles are considered “entry level” in the larger field of data, not all analysts are.  By analyzing fresh data, merging diverse reports, and communicating the results, the data scientist must be an effective bridge between different teams. 

Data analysts positions are important for firms with separate technical and business teams because they are great communicators with technical tool competence. 

A good data analyst will take the guesswork out of business choices and help the whole company succeed. As a result, the organization is able to keep a close eye on its expansion.

Data Engineer Jobs and Roles

A Data Engineer is in charge of creating the working format for data scientists and analysts. A data engineer’s job resembles that of a software engineer in many ways. This is due to the fact that a data engineer is tasked with creating platforms and architecture that adhere to software development best practices.

Data engineers work with Big Data and perform a variety of tasks such as data cleaning, management, transformation, and deduplication. A data engineer is well-versed in creating and testing software. A data engineer is responsible for handling the full pipelined architecture, including log problems, agile testing, and other technical issues.

Data Scientists Jobs and Roles

These forecasts are also used by data scientists to create goods. A recommendation system, for example, forecasts what you like, a ranking system, the order of popularity, and NLP, the meaning of a sentence. These products are created by data scientists to help businesses solve problems rather than make decisions.

When it comes to understanding data, data scientists bring a fresh viewpoint and approach. While an analyst can describe trends and translate them into business terms, a scientist can ask new questions and create models to make predictions based on fresh data.

Because the importance of data science differs from firm to company, compensation might vary significantly.

Difference between Data Engineer and Data Scientist

Data Engineers

Data engineers are in charge of creating, testing, and maintaining data ecosystems. These ecosystems are important and need to be confidential for businesses, particularly data scientists, whose job it is to examine data in order to develop prediction algorithms. As a result, we might say that data engineers are important to data scientists.

Data engineers are typically software engineers who are fluent in programming languages such as Python, Java, SQL, and Scala. They are eligible for the role if they have undergraduate degree in mathematics or statistics, which allows them to apply various analysis methods to commercial challenges.  Most companies look for candidates with a bachelor’s degree in computer science, applied math, or information technology when hiring data engineers.

Data Scientists

Data scientists are focused on getting hands-on insights from the data that data engineers have produced for them. They conduct online experiments, establish hypotheses, and uncover trends and forecasts for the business using their understanding of statistics, data analytics, visualization of data, and machine learning algorithms.

They also meet with company leaders to learn about their special needs and communicate complex findings in a way that can be understood by a business audience, both verbally and visually.

They are eligible for the role if they have undergraduate degree in mathematics or statistics, which allows them to apply various analysis methods to commercial challenges. Data scientists usually deal with vast amounts of data and no specific business problems to tackle.

So, a bachelor’s degree in computer science or a related discipline such as mathematics, economics, statistics or information technology is required for many data engineers and data scientists. Employers frequently want candidates with advanced degrees.

Data Analyst to Data Engineer

As a data analyst, the job isn’t particularly exciting, and there aren’t many chances in the near future. In the data industry, a common career path question is how to transfer from a data analyst to a data engineer.

While the work is difficult for persons who have no experience with manipulating data or statistics, it is significantly less complex and technical than the work of other members of a data team, such as a data engineer or data scientist. As an analyst, your primary responsibility is to convert complex numerical data into a manner that non-statisticians in the organization can comprehend. As an analyst, the knowledge you will obtain on the job will be different.

While your path from analyst to data or software engineer may differ significantly from that of others. Remember to use your analyst role to get skills, information, and experience that will allow you to transition into engineering in the future.

Lastly in any industry, moving from an entry-level position, such as analyst, to a senior position can take several years and requires a lot of devotion. Despite the fact that you will most likely face setbacks and struggle with specific areas along the route, remember to consider each experience as a learning opportunity.


Technology is moving in a light speed trajectory and so the job roles. The world is focusing on new opportunities and making career switches to avail new opportunities. Talking about roles of Data Engineers, Data Scientists and Data analysts are important to every tech company that is on a commercial level. However, the career opportunities as a Data Analyst might not be as exciting as compared to other tech roles.