Data Architect vs Data Engineer

The demand for data architecture and data engineers is higher day by day. Sometimes we use data architect and data engineer mutually. Data architecture and data engineering are closely related to each other. Moreover, many people are frequently confused about these topics. So, we explain data architect vs data engineer in detail.

Data Architect

A data architect is in charge of formulating the data strategy of the company. In addition, a data architect is defining the data management quality. They also define the principles on which the organization is work. The data architect also designs the data blueprint. Moreover, data consumers follow and execute this data blueprint. They create logical and physical data assets. According to the requirements of a company. In addition, they are also responsible to set data policies. The data architect has obtained experience navigating complex business and design solutions. That is implemented by the data team. 

Responsibilities of Data Architect

The primary responsibilities of a data architect are providing huge technical expertise for designing, creating, and managing data. They also deploy a large amount of data in the organization.

They are responsible for,

• Designing, developing, and implementing data. Moreover, the data source, data flow, principles, and data security policies. They also translate the overall company data strategy
• Cooperate with data engineers, data scientists, and colleagues to execute data strategy.
• Define data architecture design in the organization that guides the data structure.
• Guiding data team in developing more secure, high-performance, dependable big data. In addition, they also guide the data team for services and analytics software.

Data Engineer

A data engineer is in charge of designing, maintaining, and optimizing data architecture. A data engineer is also responsible for data management. Moreover, they are responsible for data collection, transmission, and access. In addition, data engineer creates a strategy that converts raw data into usable formats. They do it, for data consumers and data scientists utilize this data. The role of the data engineer evolved to control the core data aspects. They do it, for software engineering and data science. They use principles of software engineering to develop algorithms. That algorithm automates the process of data flow. They also cooperate with data scientists to build machine learning. In addition, they built analytics infrastructure from testing to deployment.

Responsibilities of Data Engineer

The main responsibility of a data engineer is to make sure that data is readily available, and secure. Furthermore, stakeholders access this data easily when they need it.

They are responsible for,

• Building and keeping up data infrastructure for optimal production, and transformation. They were also responsible for loading data from a collection of sources. These sources are Amazon Web Services (AWS) and Google Cloud Big Data platforms.
• Make sure data accessibility at all times. They are also responsible for implementing organization data policies regarding data privacy and closeness.
• Cleaning and arguing data from primary and secondary sources into formats. These formats can be efficiently used by data consumers and data scientists.
• Cooperate with engineering teams, data scientists, and other stakeholders. They will do it, to understand how data can be used to meet business needs.