In addition to extensive experience in the higher education sector, the Data Architect should have the following qualifications:
- Deep proficiency in data warehousing technologies and data integration pipelines using both ELT and ETL processes
- Experience with data modeling, including schema design, data models, data flow diagrams, data dictionaries and metadata repositories
- Experience designing and building complex data solutions using both SQL and non- SQL databases
- Experience with Application Programming Interface (API) for custom workflows, microservices, and integration
- Familiarity with Data Hub, Data Lakehouse, Data Fabric, and Data Mesh concepts and hybrid (on premises + cloud) data infrastructures
- Knowledge with data science, machine learning, and statistical analysis techniques to build predictive models, perform advanced analytics, and derive actionable insights from data
- Experience and knowledge building Data Catalogs and Data Marts
- Strong programming skills in languages such as Python, R, or Scala as well as Java
- Experience collaborating with cross-functional teams to define data standards, guidelines, and best practices
- Knowledge of data governance, data security, and compliance standards.
- Creative problem-solving skills and strong analytical abilities
- Excellent communication skills with the ability to convey complex, technical information in an understandable manner
- Ability to logically troubleshoot issues, determine root causes, and present suggested solutions clearly and concisely
- Familiarity with data visualization tools (e.g., Tableau, Power BI), and data pipelines that incorporate them
- Familiarity with AI capabilities across various LLMs and some experience in integration of Data Hub/Lake with AI tools.
The Data Architect will evaluate crucial aspects of data ecosystem, including:
- Business Goals and Objectives
- Data Requirements and Needs
- Current Data Infrastructure
- Data Sources and Integration Points
- Data Quality and Integrity
- Data Governance and Compliance
- Security and Privacy Measures
- Data Lifecycle Management
- Metadata and Cataloging
- Scalability and Performance
- Data Architecture design and models
- Regulatory and Industry Compliance
Additionally, they will:
- Support the Senior Project Director and Implementation Leads with project plans, deliverables, and project artifacts
- Support the Business Analysts and Implementation Leads with project plans, deliverables, and project artifacts
- Maintain project library of project plans, deliverables, and project artifacts
- Identify areas for project improvements and efficiencies
- Prepare artifacts and presentations for governing bodies as defined in the Governance Management Plan