Data Architect

Data Architect Job Profile

What Is a Data Architect?

Data Architects store and process data in such a way that the company can integrate it perfectly. They are responsible for designing and building the data architecture.

Data Architecture (also called information architecture) is a subfield of IT architecture. It considers the underlying structures and processes associated with data or information within a company — how data is:

• Captured
• Stored
• Organised
• Integrated

Data Architecture is the responsibility of the Data Architect. Its goal is to translate business requirements into data and system requirements, and to manage data and its flow within the enterprise. Today, many organisations are modernising their Data Architectures to lay the foundation for digital transformation and to take full advantage of AI opportunities.

What Are the 6 Principles of Data Architecture?

1. Data is a common good: Data Architecture should break down departmental data silos and provide a complete picture of the business to all stakeholders.
2. Users need appropriate access to data: A modern Data Architecture must provide interfaces that allow users to easily consume data with the appropriate tools.
3. Security is essential: Modern Data Architectures are designed with security in mind and support data policies and access controls at the raw data level.
4. Common vocabulary: Core data sets such as product catalogues, fiscal calendars, and KPI definitions require a common vocabulary to avoid conflicts during analysis.
5. Data curation: Invest in core curation capabilities — modelling key data relationships, cleansing raw data, curating relevant dimensions and metrics.
6. Increase data flow agility: Reduce the number of data movements required to lower costs, improve data timeliness, and increase business agility.

What Components Are Part of the Data Architecture?

• Data pipeline: The process by which data is collected, moved, and coordinated — including collection, enhancement, storage, analysis, and distribution.
• Cloud storage: Many modern architectures rely on public, private, or hybrid cloud instances for agility and flexibility.
• Cloud computing: Used for data analysis and management beyond simple storage.
• APIs: Application Programming Interfaces that make it easier to share data across systems and applications.
• AI and ML models: Used to automate tasks such as data collection or labelling, and to deploy AI at scale.
• Data streaming: Continuous flow of data from source to destination, processed and analysed in real time.

What Are the Responsibilities of a Data Architect?

The tasks of a Data Architect range from conceptual and strategic work to hands-on technical activities:

• Designing, building, and evolving data architecture aligned with organisational processes
• Translating business requirements into data models and system specifications
• Selecting and implementing appropriate data storage technologies (relational, NoSQL, data lakes, data warehouses)
• Designing ETL/ELT pipelines for data movement and transformation
• Establishing data governance policies, security frameworks, and access controls
• Evaluating and implementing cloud data platforms (AWS, Azure, GCP)
• Collaborating with Data Engineers, Data Scientists, and business stakeholders
• Documenting data architecture decisions and maintaining architectural blueprints
• Advising on data quality, data lineage, and master data management

What Skills Does a Data Architect Need?

Technical:

• Database design — relational (SQL Server, PostgreSQL, Oracle) and NoSQL (MongoDB, Cassandra)
• Cloud architecture: AWS, Microsoft Azure, Google Cloud Platform
• Data modelling and data warehousing (Kimball, Inmon methodologies)
• ETL/ELT tools and data pipeline frameworks
• Data governance and security principles (GDPR compliance)
• Programming: SQL (expert level), Python

Soft skills:

• Strategic thinking — aligning data architecture with long-term business goals
• Communication — presenting architectural concepts to technical and non-technical audiences
• Problem-solving — designing for scalability, performance, and maintainability
• Collaboration — working across engineering, analytics, and business teams

What Does the Requirement Profile of a Data Architect Look Like?

Depending on the organisation for which a Data Architect works and the process of designing the Data Architecture, the requirements for the position can vary greatly. The basic requirements for a Data Architect range from being very knowledgeable in data modelling, database management systems, and information management to having specific SQL and database management skills. In most cases, a degree in computer science or a degree in business administration should be available. Due to the strategic nature of the job, a conceptual approach and structured mindset is required of the Data Architect, as well as relevant work experience.

What Is the Difference Between Data Architecture and Data Modelling?

According to the Data Management Book of Knowledge (DMBOK 2), Data Architecture defines a plan for managing data assets. Data Architecture aligns with business strategy to define strategic data requirements and designs to meet those requirements. Accordingly, data modelling is “the process of discovering, analysing, representing, and communicating data requirements in a precise format (data model).”

Both Data Architecture and Data Modelling aim to bridge the gap between business goals and technology. Data Architecture, however, is about a macro view that aims to understand and support the relationships between organisational characteristics, technologies, and data types. Data Modelling, on the other hand, focuses on a focused view of a particular system or business case.