Data careers are becoming increasingly important and popular all across the globe, simply because “data” is the new currency of the data economy. The pandemic gave the needed push to accelerate the digital transformation of global businesses, and currently, the primary market differentiator is an enterprise’s data infrastructure readiness. This data infrastructure comprises systems, processes, tools, and qualified manpower. In today’s market, both the data architect and data engineer are more in demand than the data scientist.

The data architect and data engineer work in tandem – conceptualizing, visualizing, and then building an Enterprise Data Management Framework. The data architect visualizes the complete framework and creates the blueprint, which the data engineer uses to build the “digital framework.”

The data engineering role has recently evolved from the traditional software-engineering field. Recent Enterprise Data Management experiments have proven beyond doubt that these data-focused software engineers are needed to work along with the data architects to build a strong Data Architecture. Between 2018 and 2020, the growth of data engineers was around 122 percent in response to a massive data industry need.

Descriptions of Two Complementary Job Titles

Data architects have the capability to “put order in data chaos.” Without this, enormous piles of business data are useless. Data architects design the “blueprint” for organizational Data Management. Each Data Science team requires a data architect to visualize, design, and prepare data in a framework that can be utilized by data scientists, engineers, or data analysts. Very often, these experts have academic degrees in a computer discipline, years of systems or application development work, and deep knowledge about Information Management.

Typically, an entry-level data professional will have to go through grueling years of data design, Data Management, and data storage work before qualifying for a data architect’s position. According to a report from Payscale.com, data architects enjoy a median salary of $111,139 per year.

On the other hand, data engineers assist the data architects to build the working framework for data search and retrieval, which both scientists and analysts can use for their work later. In most cases, data engineers earn their qualifications from the myriad of certificate courses available from professional training vendors. In the Big Data world, these highly specialized engineers are responsible for building and testing maintainable Enterprise Data Architectures. Data engineers command an annual median salary of $90,286.

Data architects and data engineers together put a usable Data Architecture in action for the organizational Data Management teams. Despite complementary roles in the Data Science world, these two professionals can be quite different in their daily job functions.

Skills Required for a Data Architect vs. Data Engineer: 2021 Updates

Here are some steps an aspiring candidate can take in 2021 to become a data architect:

1. Earn a degree in Computer Science, Computer Engineering or a related field.

2. Develop some of the technical skills provided below:

• Data mining
• Machine learning
• Data visualization
• Predictive modeling, NLP, and text analysis
• User interface and query software (e.g. IBM DB2)
• Application server software (e.g. Oracle)

For the complete list of relevant technical skills, refer to How to be a Data Architect in 2021.

Here are some essential business skills for data architects:

• Problem-solving skills
• Professional communication skills
• Team development and management skills
• Industry knowledge

3. Optional certifications to grow in data professions:

• Certified Data Management Professional (CDMP): Developed by the Data Management Association International (DAMA), these certifications add credibility to any data architect’s résumés. The CDMP is offered at four levels. Refer to the above link for details
• Salesforce Certified Data Architecture and Management Designer
• TOGAF^® 9 Certification Program
• IBM Certified Data Architect – Big Data

Here are some steps an aspiring candidate can take in 2021 to become a data engineer:

Although data engineers frequently join the profession with an undergraduate degree in science, math, or business, an ambitious professional will have to take some extra steps to succeed and prosper in data engineering. Some such steps are provided below:

1. Develop computer engineering, data analysis, and big data skills.
2. Take additional certifications in engineering or big data.
3. Think of earning higher degrees in computer science, computer engineering, applied mathematics, physics, or any other related field.

The Working Lives of a Data Architect vs. Data Engineer: Contrasting Roles

Data architects often use their hands-on skills in a wide variety of Data Management fields like data modeling, data warehousing, database management, and ETL tools. Certain programs require that qualifying candidates demonstrate expertise in specific areas like data lineage or data replication.

The data architect’s role has evolved somewhat over the years, and the emergence of the data engineer has enabled the architect to move away from building the data framework to visualizing it. In recent years, the data architect has evolved into a “visionary,” due to expert knowledge of database architecture and query languages like Spark or NoSQL.

Data Analyst vs Data Engineer vs Data Scientist suggests that a data architect is only a data engineer with more experience. The data engineer uses the organizational data blueprint provided by the data architect to gather, store, and prepare the data in a framework from which the data scientist and data analyst work. This approach relieves the data scientist or the data analyst of massive data preparation work, allowing them to concentrate on data exploration and analysis.

The data architect and the data engineer may acquire same or very similar expertise in database architecture over time, but they use this knowledge differently. While data architects provide knowledge and guidance in handling disparate data sources from varied databases, the data engineers take the architect’s vision to build and maintain the Data Architecture for the enterprise data professionals.

An interesting comparison between the two roles describes the data architect as a person who, with deep database expertise, can visualize a priori how changes in data acquisitions can impact data use. In contrast, the data engineer, with deep software-engineering expertise, can build and maintain a data system that compensates for those changes.

Major Differences Between Data Architect vs. Data Engineer Roles

Differences between the two roles include:

• Data architects conceptualize and visualize data frameworks; data engineers build and maintain them.
• Data architects guide the Data Science teams while data engineers provide the supporting framework for enterprise data activities.
• Once upon a time data architects fulfilled the roles of data engineers; since 2013, data engineering as a separate career field has experienced tremendous growth.
• Although both the data architect and the data engineer are experts about Database Management technologies, they use their knowledge very differently in their respective roles.
• The Dynamics of Data Roles & Teams confirms that data professionals without software-engineering knowledge will not make good candidates for data engineers. Thus, it is safe to conclude that while seasoned data professionals may aspire to become data architects, these same professionals may not qualify for data engineering positions without the requisite software-engineering background.

Which One Do You Prefer to Be?

Given the exponential rise of data sources and incoming data pipelines, the growth of data architects and data engineers is inevitable in the coming years.

• The Data Architect is Still Evolving: Is Data Science really the up-and-coming profession of the 21^st Century? Or is Data Management dead thanks to the overwhelming advancements in machine learning and deep learning? What does the future really hold for data professionals? Amid much speculation, the data architect role is increasingly transforming technology into business value. In the DATAVERSITY® webinar Data Architect vs. Data Engineer vs. Data Modeler, the speaker is known for helping organizations earn rich business benefits from their data stockpiles.

• Data Professionals without Software Engineering Backgrounds Not Cut Out for Data Engineering Roles: the mainstreaming of big data technologies across industry sectors has necessitated data engineers on Data Science teams. These engineers must demonstrate a combination of database management knowledge and software engineering skills. However, not every software engineer is expected to develop an interest or expertise in data technologies.

So You Want to be a Data Engineer? states that the primary responsibility of the data engineer is to supply timely and trustworthy data to support all analytics and reporting activities conducted by other data professionals within the organization. To this end, the data engineer develops and maintains the enterprise data framework for continued use. A Self-Study List for Data Engineers and Aspiring Data Architects contains some interesting resources for aspiring data architects and data engineers.

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