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Data Engineer vs. Data Architect

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What is a Data Engineer? What does He do?

Data Engineers are data scientists who create and manage the analytics infrastructure. They are software engineers who design and build the data pipeline, integrate the data from multiple systems, and manage the databases and supporting systems. Data Engineers integrate and clean the data for use in analytics applications. They perform complex queries on the big datasets and create warehouses for reporting or analysis. Data Engineers are much more than Data Analysts as they focus on the design and architecture rather than modelling or analytics.

A Data Engineer works with other members of the data science teams, to improve data transparency and develop algorithms to make raw data more usable for analytics. The Data Engineer is critical for companies handling big data, where the analytics architecture is complex. Data Engineers construct and test the system for scalability and prepare the data for analytical use from real-time streaming data.

Responsibilities:

Data Engineers extract, clean and curate data; process and update third-party data sources; build datasets that answer key business questions; implement data management projects; manage data pipelines; develop best practices for data management and reporting; organize and align the Data Architecture with the requirements of the data science practitioners, develop, test and maintain Data Architectures, perform ETL, install data warehousing solutions, conduct Data Architecture testing, construction, and development.

What is a Data Architect? What does He do?

The Data Architect designs, creates, deploys, and manages the blueprint of an organization’s Data Architecture. He constructs the analytical framework; plans the data management strategy and the tools to be used for analysis and modelling, and creates rules and standards for the governance of the database. A Data Architect is an IT professional and a Data Scientist who uses expert skills in computer design to develop databases, for data storage and analysis of big data. He sets out how the data is stored, integrated, and consumed by various data entities, IT systems, and applications. He ensures that a formal data standard is adhered to and that the company’s data assets conform to the defined Data Architecture and goals of the business.

Data Architects are creative problem-solvers with a variety of programming tools at their disposal to design and innovate solutions for data governance.

Responsibilities:

Data Architects define the Data Architecture framework, standards, and principles; delineate the reference architecture, design data flows,  maintain the metadata registry, oversee data management, optimize databases and data sources, translate business requirements into technical specifications, including data streams, integrations, databases, and data warehouses, and collaborate with multiple departments, stakeholders, database administrators and data scientists, and external vendors to achieve the strategic data management goals of the company.

They develop the Data Architecture to capture, integrate, organize, centralize and maintain data for Data Warehousing solutions, ETL, and data modeling.

Data Engineer vs. Data Architect

The Data Engineer and Data Architect roles are closely related. Both are Data Scientist job roles.  Both the positions work together to create and oversee the enterprise data management framework for use by data science teams, and data analysts.

Historically, Data Architects fulfilled the roles of Data Engineers; but since 2013, Data Engineers have emerged as a powerful job role in enterprise architecture.

Data Engineers assist Data Architects in building the data framework using data search and retrieval. They have deep software-engineering expertise and work with cutting-edge technologies in big data: data lakes, cloud platforms, and data warehouses in the cloud. While the Data Architect is more of a “visionary” who uses several years of experience working with multiple technologies and tools, and deep database expertise to create the data framework and the data pipelines; the Data Engineer uses his software engineering skills.

The Data Engineer and Data Architect work together to conceptualize, visualize, and build an Enterprise Data Management Framework. They have similar expertise in Database Architecture but they use it differently. While Data Architects guide in managing disparate data sources, the Data Engineers use the architect’s vision to build and maintain the data pipelines for the enterprise data professionals.

The key differences between the two roles are as follows:

  • Data Architects visualize and design the data frameworks; Data Engineers build and maintain them.
  • Data Architects have Data Architecture experience, while Data Engineers have software engineering knowledge. While experienced data professionals can become Data Architects, the same professionals may not qualify for Data Engineer job roles without a software engineering background.

Thus, the Data Engineer implements and manages the Data Architecture designed by the Data Architect, and uses the blueprint to build the digital framework.

What would you prefer to be: Data Architect or Data Engineer?

The exponential rise of data has led to the demand for both Data Architects and Data Engineers.

If you are wondering what job role suits you, you must examine the following:

Experience: Do you have work experience as a data practitioner? Then you can qualify to be a Data Architect.

Background: What is your background? If you come from software engineering, then Data Engineer would be the right career choice. If not, and you know Data Architecture, you can aspire to be a Data Architect.

With more companies handling big data, Data Engineers are here to stay. But you must demonstrate knowledge of Database Management and software engineering to aspire to be a Data Engineer.

Conclusion

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1 COMMENT

  1. The references to only males in this article are frustrating and inaccurate.
    “What is a Data Architect? What does He do?” and many more…

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