Overview of Data Architect Role
Data Architecture Expert
The role of a Senior Data Architect involves designing and implementing technology solutions that align with an organization's overall business strategy.
This requires a deep understanding of both current and emerging technologies, as well as a keen awareness of the organization's goals and objectives. The successful candidate will be responsible for creating a holistic view of the IT infrastructure, considering factors such as scalability, security, and interoperability.
A key aspect of this role is developing and maintaining architecture blueprints and documentation that serve as a reference for various stakeholders. This documentation includes system diagrams, data models, and integration specifications, providing a clear roadmap for the implementation of IT solutions.
Collaboration with other IT professionals, such as developers, system administrators, and project managers, is crucial to ensure effective communication between different teams and guarantee the successful integration of technology solutions and the delivery of projects on time and within budget.
Minimum Requirements
* Proven Experience: At least 7 years of experience as a Data/Applications Architect, demonstrating a successful track record of aligning IT strategies with business objectives.
* Cloud-Based Technologies: Experience with cloud-based technologies and microservices.
* Technical Skillsets: Applied the technical skillsets and competencies as the primary part of their role, within the last 1 year.
* Qualifications: A minimum of qualifications in a relevant field equivalent to European EQF level 7.
* Language Fluency: Fluency in the English language.
Key Deliverables
* Conceptual Modelling: Proficiency in conceptual, logical, and physical data modelling.
* Database Management: Experience with entity-relationship diagrams, data flow diagrams, and other modelling techniques, as well as expertise in various database management systems.
* Data Security: Understanding of database architecture, indexing, and query optimization, as well as knowledge of data security principles and best practices.
* Data Governance: Ensuring compliance with data regulations and implementing access controls, encryption, and data masking techniques.