How to Become a Database Architect

January 20, 2022

Designing a new database or modifying an existing one.
Ensuring data integrity and security.
Optimizing the performance of the database system.
Guiding big data initiatives.

Database architects are highly valued employees because they play a crucial role in improving business results, helping organizations collect, store, and utilize the data that’s become so important to modern businesses.
Database architects are well-paid, earning a considerable income for the work that they do. According to BLS, database architects earn an average salary of $101,000.
Demand for trained database architects is growing. The Bureau of Labor Statistics reports that the employment of database administrators and architects is expected to grow by 9% between 2021 and 2031.

Systems Analyst: This job title could include database architecture work, as systems analysts may be in charge of designing and implementing database systems themselves, or the systems that interface with databases. In general, this role entails understanding the company’s business needs and then translating those needs into a technical design, sometimes, for databases.

Database Developer: A database developer is in charge of writing, modifying, and maintaining the database code. In some cases, the database developer may be a junior role to database architect, taking the architect’s plans and then putting them to work by actually building the database, with the architect overseeing the construction. However, some database developers may serve as database architects too, designing the system, then building it themselves instead of handing off the work to others.

Database Manager: This professional is typically in charge of maintaining databases and may be responsible for just one, or several, or even many different databases. The database manager is likely to be in charge of implementing data management practices, monitoring database performance, helping other professionals extract and examine data, and ensuring that the database and the data it stores remain accurate, reliable, and available at all times.

Data Analyst/Scientist: These individuals analyze large amounts of data to identify trends or specific patterns in the data which they can then use to guide business strategy. Data analysts and data scientists tend to collaborate with a group of other professionals, such as database administrators and developers, who can assist them in gaining access to the necessary information, which they then analyze for insights.

Database Administrator: The database administrator is in charge of creating and managing database users, permissions, and security roles. Their job is to ensure that only authorized users have access to company data, and their primary role tends to be managing access to the information stored in the database.

Data Engineer: This role is similar to that of a database developer, but data engineers specialize in big data technologies such as Hadoop or Apache Spark—programs designed to analyze very large volumes of data in real-time. The data engineer’s job is to collect, manage, and convert data into useful information used for powering data-driven business decisions.

Data Modeler: The person in charge of creating the database’s conceptual, logical, and physical data models. A data modeler’s primary responsibility is to ensure that an organization’s data is being put to use properly and that it’s capable of being utilized to help inform important business decisions.

Data Warehouse Engineer: This position is in charge of designing, constructing, and maintaining the data warehouse, which is a type of database that stores historical data that can be used for analytical purposes.

Designing and implementing databases: This is probably the most critical task for a database architect, who must understand the company’s business needs so that they can design a system that meets those needs as efficiently as possible. This includes choosing a database management system, optimizing the data model and queries to improve performance, designing indexes for speeding up lookups, etc.

Consulting with clients to understand their needs: This involves understanding the business, its goals, and needs, as well as what data is needed to support those goals. Successful database architects gather information about business processes and activities to help guide their design philosophies, ensuring that the database they build will serve the company’s needs.

Developing a data model: A data model determines what information any given database will collect, how it will be stored, and how it is related to the organization’s various business units. It’s also like writing up a statement of purpose message for the organization, explaining the specific structure of the database under construction. You can think of a data model as being like a graphical representation of what data will be collected, and how the data will be stored, including the structure of tables, fields, indexes, etc.

Designing queries: A query specifies which records should be included in the results and what operations (e.g., grouping, sorting) should be performed on those records during the retrieval process.

Analyzing database performance: Database architects must monitor how well the database performs and identify any bottlenecks that might cause it to operate slowly or that could cause it to fail. They also need to make sure there is enough server memory available for processing queries quickly and that the data is being backed up properly.

Creating and overseeing ETL processes: ETL (Extract, Transform, Load) processes are used to move data from one system to another. The architect needs to develop a process to extract the data from the source system, transform it into the correct format, and load it into the target system.

Optimizing queries: Database architects need to be able to write efficient SQL queries that efficiently access the data, allowing anyone who needs access to the stored information to gain access to it and extract it so it can be processed or analyzed in some useful way.

Creating reports: Architects may be required to create custom reports either on-demand or as part of a regular ETL process (Extract, Transform, and Load). This ensures that the data stored in the database is available and accessible for whatever organization purpose it’s been collected to satisfy.

Troubleshooting and resolving database issues: Database architects are often asked to help resolve issues with the databases that they’ve constructed, including fixing a corrupted database, bringing one back online that has gone down, fixing problems accessing data, and optimizing performance.

Collaborating with other teams: Database architects should have good communication skills and work well in cross-functional teams. They need to be able to communicate effectively with other teams in the organization, including developers, product managers, and the organization’s executives.

Train employees: While database architects typically don’t spend much time training new hires, they may do initial training for existing staff members when an important deadline is approaching or a major change needs to be made to the system.

Keeping up to date: Database architects also need to keep up with new technologies and changes in the industry, technology, platforms, and organizational requirements. This part of the process can be extremely time-consuming, as database technology can change both dramatically and rapidly.

Documenting: As part of their job, database architects need to document all aspects of the system they design. This includes documenting the data model, describing how the system works, and creating user manuals and other documentation useful for anyone who will be interacting with their databases.

Database programming skills
Knowledge of data modeling principles and concepts
Database management systems (DBMS)
Relational algebra
Entity-relationship model
A strong understanding of data structures and algorithms
Experience with multiple programming languages such as Java, C++, Python, and Ruby
The ability to design SQL queries for complex datasets

Data mining
Statistical analysis
Database management
Systems design
Business intelligence

Data modeling
SQL
T-SQL
ETL processes
Performance tuning
Report writing

The Fundamentals of Quantitative Analysis
Foundations of Data Analytics
Introduction to Business Intelligence
Data Mining and Visualization
Predictive Analytics
Business Analytics

Amazon Web Services (AWS) Certified Data Analytics – Specialty
Cloudera Data Platform Generalist Certification
Data Science Council of America (DASCA) Associate Big Data Engineer
IBM Certified Solution Architect – Cloud Pak for Data v4.x
IBM Certified Solution Architect – Data Warehouse V1
SAS Certified Big Data Professional

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