The Key Point of Analytics Engineer

March 31, 2023 - Aptaworks

To fulfill business intelligence and data analysis requirements, organizations typically provide two roles: Data Engineer (Engineers) and Data Analyst (Analysts), with clear scope division. Engineers are responsible for the infrastructure and availability of data and rely on their expertise in providing the data needed by Analysts. Analysts process the provided data to gain understanding and conclusions that can be presented to users.


Difference between Engineers and Analysts

In practice, Engineers are closer to data system, thus understanding the available data better, while Analysts are closer to business users, thus understanding the desired data needs better. These different perspectives often create problems between the two roles, such as when data is not available or changes from its intended form. Often, prepared data must be corrected by Engineers or Analysts, resulting in slow, obstructed, or even unfinished work.

The above scenario is commonly found in traditional data teams. Traditional data teams usually work on non-diverse data systems, and as the time evolves, existing data systems become more diverse, making an Engineer’s task more challenging. This data system diversity is why Engineers sometimes struggle to fulfill the data request made by an Analysts because the data must be transformed into proper data that can be used by the Analysts. Not only because the system of data has become diverse nowadays. Sometimes the problem can be initiated by the Analyst, such as, the Analysts do not know what to analyze with the data that has been provided by the Engineer


What is Analytics Engineer?

From the above case, we can observe that there is one role as equally important as the other two that can overcome this problem. An Analytics Engineer is a reliable role that can connect Engineers and Analysts. Before we move forward, it is better for us to get to know about Analytics Engineer in general. Analytics Engineer is a specialized type of Data Engineer who focuses on building and maintaining data pipeline for analytics and data science purposes. Analytics Engineer will also collaborate closely with Analysts and stakeholder to understand their data requirements and develop customized solution to meet their needs. Overall, the role of Analytics Engineer is quite critical for enabling organizations to make data-driven decisions and gain valuable insights from their data by modelling data, transformed data, and maintain the documentation of data.

Many of you might be wondering about the future-proof of the Analytics Engineer role. What can I say to this time is Analytics Engineer has a future-proof role because, data is becoming increasingly central to business decision-making across industries. As a result, organizations will continue to invest in analytics and data engineering to help them make sense of the data they collect and generate insights that drive business value.


Scope of Work

The rate of technological advancement is increasing, which means that there will be a growing need for professionals who can stay abreast of these changes and design and implement solutions that leverage the latest technologies. Analytics Engineer also have scope of machine learning, artificial intelligence, and big data analytics. As these fields continue to evolve, there will be a growing demand for professionals who have the skills and knowledge to work with these technologies.

Lastly, Analytics Engineering is a highly specialized field that requires a unique combination of technical, business, and communication skills. As such, it is unlikely to be easily automated or outsourced, meaning that there will continue to be a need for skilled professionals in this area.



The roles of Data Engineer and Data Analyst often face problems due to differences in perspectives and understanding of data. An Analytics Engineer, a specialized type of Data Engineer, can bridge the gap between the two roles and develop customized solutions for data pipeline, analytics, and data science purposes. The role of Analytics Engineer is critical in enabling organizations to make data-driven decisions and gain valuable insights from their data. The Analytics Engineer role is future-proof due to the increasing importance of data in business decision-making, technological advancements, and the need for a unique combination of technical, business, and communication skills.

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