Data Architect Vs. Data Engineer: What’s the Difference? Which Is Better?
Data architects and Data Engineers look into various aspects of data science. Though both job profiles form the core element of data science, yet they are different.
Data engineers make sure that all data are thoroughly checked, inspected and verified before entering into official records for further analysis, while data architect looks closely into various aspects to facilitate the smooth process of data extracting and structuring them accordingly.
Their primary responsibility is to inspect data warehouses and relational databases to scrutinize the accuracy of data. The ultimate aim of both data architects and data engineers is to extract quality data for analytical purposes.
Data Professionals—Key Statistics
According to BLS (Bureau of Labour Standard, US), data professionals are in great demand these days. The growth in data-related jobs is likely to grow around 9% from 2021-2028.
Currently, more than 50% of data professionals are residing in the United States. There’ll be a massive demand for both data architects and data engineers across the other part of the world.
Why Are Data Professionals In Demand?
Over the last few years, the demand for data professionals has considerably increased. Data professionals are the ones who can conceptualize and process raw data into meaningful information. It helps businesses earn quality leads which can be converted into sales later. By 2025, IDC (International Data Corporation) stated that the present data capacity of servers will increase ten times. Only experienced data professionals can manage such huge data and extract meaningful information from the same. Both data engineers and data architects have to work together to collaborate for the fulfillment of data management goals.
Which of the two roles—Data Architect or Data Engineer—is best for you?
The data architecture function demands years of expertise in a previous data-related role; both roles necessitate a thorough knowledge of database systems, data processing tools, and prior experience working with big data. Keep this in mind while choosing a profession or recruiting. You must first comprehend the distinctions between the jobs in order to assemble a team for data management that works well.
If a candidate is being interviewed for a position as a data engineer, ask about their expertise creating software and APIs as well as their knowledge of various databases, data wrangling methods, and data processing strategies.
Conversely, when interviewing data architects, make sure to acquire a feel of their “data mindset” by asking about the data projects they have previously managed. Observe this
Your data management team will be led by a data architect, to whom you should feel comfortable handing power.
[Read more: An Overview of Big Data Architecture]
Job Profile of a Data Engineer
A data engineer can be hired to monitor any aspect of a data project. Be it strategizing data warehouses or verifying data to frame analytical programs based on data-driven information, a data engineer is a multi-tasking person with several responsibilities that rests on his shoulder.
It is the duty of a data engineer to process a large volume of data and draw inferences from the same for business analytics. Data engineers need to have strong computational and analytical skills.
Job Profile of a Data Architect
Data architects are responsible for the overall maintenance of the data warehouse and storing relevant data on the servers. They have to also ensure that data is properly stored and out of reach of people outside the organization.
Data architects look beyond data modeling and data mining. Data architects have to work in tandem with database administrators, developers, and engineers to create a robust data-driven app, which can help the company achieve its goals.
[ Read more: How Can Small Businesses Leverage Big Data?]
Data Engineers and Data Architects: Top Skills
Extract, Transform, Load (ETL)
Data Engineer: Other Important Skills
A critical thinker
Immaculate communication skills
Meticulous in operational skills
A team player
Ability to work under intense pressure
Data Architect: Other Important Skills
Strong problem-solving skills
Good listening skills
Good Presentation skills
Complete domain knowledge
Certification Process for Data Engineers and Data Architects
Anyone desirous of handling either of the profiles needs to have proper certifications. Without sufficient skills and professionals qualifications, It’s impossible to become a data professional.
As a data professional, you’ll handle the company’s data, which are highly sensitive in nature. So companies won’t take any chance. They will hire you as a data executive only when you have adequate academic qualifications to manage it.
It’s clear that the job profile of both data engineers and data architects is not competitive, but complementary in nature. One can’t work without the other. That is why all leading MNCs (Multinational Companies) and big enterprises hire both data engineers and data architects at their firms.
Just as you can’t run a website effectively without the help of both web developers and content writers, similarly, you can’t smoothly run your business enterprise without the help of data architects and data engineers.
FAQs (Frequently Asked Questions)
What Should I study to become a data engineer or data architect?
Complete a Certified Data Management Professional Course from Institute for Certified Computing Professionals (ICCP), Chicago. Visit its website ICCP.ORG to know more about these short-term and long-term courses and also their recognition.
Can I also study these courses online?
Yes. You’ll find several similar certification courses online offered by various companies like Google, IBM, and others. You have to personally scrutinize these online data science-related courses and their recognition before making payment (if any) or enrolling in any such courses.
Which is the most well-known course in Data Engineering?
Microsoft Certified Solutions Expert Certification course in data management and analytics is quite popular among the youth. It imbibes the right technical skills and attitudes in candidates to help them cope with the intricacies of data management tools and techniques.