Data Science Jobs: What is a Data Architect?
The demand for data science professionals is at an all time high. Companies, both large and small, are clamoring for the best talent in the market to help them efficiently capture, process, and analyze massive data sets. While smaller companies are just being turned on to the potential of data analytics, larger companies have several different sources of data and a large amount of data activity. High-performing companies, as revealed in a study by McKinsey, place critical importance on this wealth of data to drive decision-making at multiple levels of the organization. Data is the backbone of modern management and strategy.
One of the most in-demand jobs within data science is that of the data architect. Companies looking to implement any sort of robust data strategy need a data architect who knows their way around large scale databases, data analysis and machine learning, using programming languages. These types of companies also need the data architect to help them figure out how the data—both structured and unstructured—should be stored and how it should be integrated with different IT systems.
At the University of Virginia’s School of Data Science, we offer the online Master of Science in Data Science (MSDS) program which gives students a solid foundational knowledge of data management while also teaching students practical skills such as machine learning and programming languages so that they can prepare for a career as a data architect.
What is a data architect?
To understand the role of a data architect, it is useful to look at the two other main roles within data management and business analysis and see how they are differentiated from each other. Those data professional roles are the data scientist, and data engineer.
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The data engineer has a background in software engineering and works with big data in data lakes, cloud platforms, and data warehouses in the cloud. Data engineering builds and maintains data frameworks.
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The data scientist has a background in statistics and their job involves cleaning and analyzing data, and then using the data to answer questions and provide metrics to solve business problems.
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The data architect understands both software engineering and statistics. Their job is to conceptualize and visualize data frameworks, they will also provide knowledge and guidance in handling disparate data sources from varied databases.
The data architect is an essential part of any enterprise company’s data science team, they have a holistic vision of the company’s architecture. The data architect plans and manages big data databases, they study existing data infrastructure and develop a new design to integrate current systems with a desired future state in mind. The data engineer then develops, tests, and maintains data pipelines and architectures. The data scientist will then use that data for analysis and to provide metrics.
Data architects normally start off as data engineers to gain database architecture experience and gather skills in the information technology sector and related fields. By the time they become a lead data architect, they will have a wide variety of skills, including an understanding of data modeling, data warehousing, database management, and ETL (Extract, Transform, and Load: the process of integrating raw data from various data sources into a repository such as an enterprise data warehouse).
A data architect job description will call for proven experience in data analysis and management, with excellent analytical and problem-solving abilities. The requirements often ask for a bachelor’s degree in computer science, computer engineering or relevant field. However, an MBA or an advanced degree in data science, such as UVA’s online MSDS program, will give anyone serious about becoming a big data data architect an extra edge.
What are the functions of data architecture?
Data architecture refers to the design of different data systems within an organization, and the rules that govern how the data is collected and stored. The data architecture design acts as a vision or model for the eventual interactions between data systems.
Here are the primary functions of data architecture, and how the data architect’s role relates to them:
To define information requirements within an enterprise
The data architect works with business leaders and data science teams to gather information requirements, translate them, and use those requirements to develop data-centric solutions. To come up with those solutions, the data architect creates a roadmap for how the information within an enterprise will be used, how it will flow between databases, and how it will be consumed by various business and IT customers.
To adhere to architecture standards
Much like the physical architectural industry, there are a set of industry-accepted data architecture principles and standards that must be followed when modelling a database. These standards govern modern data architecture and ensure that the data meets regulation and security needs, as well as helping achieve the goals of the business.
Part of this involves the data architect documenting data inventory and data flow diagrams to determine what can be measured, when, and how.
To focus on improving data quality, accessibility, and security
Once the data architecture has been drawn up, the job does not stop there. A data architect needs to ensure data structures comply with all local, state, federal and industry standards and regulations. This ensures best practices of data architecture enforced by the data governance committee. They also work to streamline data flows and models, while improving consistency, quality, accessibility, and security. Data architects study the databases, and their integration, and constantly look for ways to remove unnecessary costs and optimize database activity across the company’s objectives.
Finally, the data architect supports the operational use of data for business process functions and the departments that rely on the data, such as customer centricity, supply chain, product positioning, and sales efficiency.
Data architecture jobs
As mentioned above, data architects often start out as data engineers to gain experience before becoming a data architect. Data architects are key figures within a data science team, and predominantly work within large companies that are dealing with large amounts of data from multiple different sources.
The data architect will work with management, computer engineers, and other data science professionals to assess the information needs of a company and create systems that help a company optimize its data.
Data architects will need both hard and soft skills to be successful. They will be required to have a familiarity with a variety of software and data management tools, and will also have to understand programming languages, like Python, C, C++, and Java.
A large part of their job is gathering information from different groups, such as managers, marketing professionals and other IT professionals, to understand the data needs within the organization, and then to clearly define the expectations and limitations. Therefore, data architects have to be good communicators.
They also have to be analytical thinkers and creative problem solvers, as they are always looking for resolutions to both big and small issues. Any data architect job description will also likely list good time-management skills as it is crucial they are able to figure out priorities and make sure there is enough time to achieve them.
Average data architect salaries
As of November 2020, according to job board site Ziprecruiter, the average base salary for a data architect in the United States is $132,617. However, it ranges from $36,500 to $190,500, with the majority of jobs sitting in between $106,500 and $162,499.
The average big data data architect salary will depend on where the job is located, what skills the candidate has and how many years of experience. For example, the average total compensation is the highest in New York City with $145,463, 10% more than the national average.
There are also other related jobs that require the same skill set as a data architect, but have a higher average salary. Those jobs, according to Ziprecruiter, are cloud data architect, principal solutions architect, remote solutions architect, chief software architect, and IT data architect.
Prepare for a career as a data architect in the UVA online Master of Science in Data Science program
If you are a student interested in becoming a data architect, you will need to meet the educational requirements of the role, which can often involve a master’s degree in computer science or data science. The UVA online Master of Science in Data Science (MSDS) program is an excellent choice for the student who is looking to become a data architect, as the structure of the course, which takes place over two years, allows you to continue working while you study.
The online MSDS is designed to teach each student how to combine technical, quantitative, and philosophical study to shed light on complex issues using data. Upon completion of your coursework, graduates will be able to leverage computational tools to acquire, manipulate, and store data; model, analyze, and extract information from data; as well as apply important privacy, security, and ethical issues related to the use of data. All essential skills for a budding big data data architect to acquire.
If you are looking for a program that will set you on the path to becoming a data architect, consider UVA’s online MSDS program today.