Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles.
The data architect is responsible for visualising and designing an organisation's enterprise data management framework. This framework describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data.
The data architect also "provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture," according to DAMA International's Data Management Body of Knowledge.
Data architect responsibilities
According to Panoply, typical data architect responsibilities include:
- Translating business requirements into technical specifications, including data streams, integrations, transformations, databases, and data warehouses
- Defining the data architecture framework, standards and principles, including modeling, metadata, security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees
- Defining reference architecture, which is a pattern that others can follow to create and improve data systems
- Defining data flows, i.e., which parts of the organisation generate data, which require data to function, how data flows are managed, and how data changes in transition
- Collaborating and coordinating with multiple departments, stakeholders, partners, and external vendors
Data architect vs. data engineer
The data architect and data engineer roles are closely related. In some ways, the data architect is an advanced data engineer. Data architects and data engineers work together to visualise and build the enterprise data management framework. The data architect is responsible for visualising the "blueprint" of the complete framework that data engineers then build.
According to Dataversity, data architects visualise, design, and prepare data in a framework that can be used by data scientists, data engineers, or data analysts. Data engineers assist data architects in building the working framework for data search and retrieval.
How to become a data architect
Data architect is an evolving role and there is no industry-standard certification or training program for data architects. Typically, data architects learn on the job as data engineers, data scientists, or solutions architects and work their way to data architect with years of experience in data design, data management, and data storage work.
What to look for in a data architect
Most data architects hold degrees in information technology, computer science, computer engineering, or related fields. According to Dataversity, good data architects have a solid understanding of the cloud, databases, and the applications and programs used by those databases. They understand data modelling, including conceptualisation and database optimisation, and demonstrate a commitment to continuing education.
Data architects have the ability to:
- Design models of data processing that implement the intended business model
- Develop diagrams representing key data entities and their relationships
- Generate a list of components needed to build the designed system
- Communicate clearly, simply, and effectively
Data architect skills
According to Bob Lambert, analytics delivery lead at Anthem and former director of CapTech Consulting, important data architect skills include:
- A foundation in systems development: Data architects must understand the system development life cycle, project management approaches, and requirements, design, and test techniques, Lambert says
- Data modelling and design: This is the core skill of the data architect and the most requested skill in data architect job descriptions, according to Lambert, who notes that this often includes SQL development and database administration
- Established and emerging data technologies: Data architects need to understand established data management and reporting technologies, and have some knowledge of columnar and NoSQL databases, predictive analytics, data visualisation, and unstructured data
- Communication and political savvy: Data architects need people skills. They must be articulate, persuasive, and good salespeople, Lambert says, and they must conceive and portray the big data picture to others
Data architect certifications
While there are no industry-standard certifications for data architects, there are some certifications that may help data architects in their careers. In addition to certifications in the primary data platforms used by their organisation, the following certifications are popular:
- Certified Data Management Professional (CDMP)
- Arcitura Certified Big Data Architect
- IBM Certified Data Architect - Big Data
- TOGAF 9 Certification Program
Data architect jobs
A recent search for data architect jobs on Indeed.com showed positions available in a range of industries, including financial services, consulting, healthcare, pharmaceuticals, technology and higher education.
A sampling of data architect job descriptions shows key areas of responsibility such as: creating a dataops and BI transformation roadmap, developing and sustaining a data strategy, implementing and optimising physical database design, and designing and implementing data migration and integration processes.
Companies are looking for bachelor's degrees in computer science, information science, engineering, or equivalent fields, though master's degrees are preferred.
Most are looking for 8 to 15 years of experience in a related role. They want highly motivated, experienced innovators with excellent interpersonal skills, strong collaboration, and the ability to communicate effectively verbally and in writing.