BI Architect and Metadata Designer - Rosebank at Anglo American

Job Description:

• BI Architecture Design and Implementation: Develop and maintain the overall BI architecture, including data sourcing, integration, storage, and analysis frameworks. Ensure the architecture supports current and future business intelligence needs.
• Metadata Management: Design, create, and manage the metadata repository to ensure consistent use and understanding of data across the organization. This includes maintaining a business glossary and data catalogue for easy access and comprehension by users.
• Data Integration and Cleansing: Oversee the integration of data from various sources, ensuring the data is accurate, consistent, and accessible. Implement and maintain data cleansing and quality processes to guarantee reliable data for analysis.
• Analytics Support: Work with BI and data visualization tools to support the analysis of data and the presentation of insights to business users, enabling informed decision-making.
• Technology Evaluation: Stay abreast of the latest BI tools and technologies, evaluating their applicability to the organization's needs and integrating them into the BI architecture as appropriate.
• Collaboration and Leadership: Work closely with IT, data management teams, and business stakeholders to align BI strategies with organizational goals. Lead and mentor team members in BI best practices.

Qualifications:

• Degree in a relevant discipline (e.g. Information technology, computer science, data science, etc).

Technical Knowledge: 

• BI Tools and Technologies: Proficiency with BI and data visualization tools such as Power BI, Tableau, or similar platforms.
• Data Modelling and Warehousing: Deep understanding of data modelling principles, data warehousing architectures (e.g., star schema, snowflake schema), and ETL processes.
• Metadata Management: Experience with metadata management practices, business glossaries, and data catalogs.
• Programming and Database: Strong skills in SQL, and familiarity with programming languages relevant to data processing and analysis (e.g., Python, R).
• System Integration: Knowledge of system integration techniques and the ability to incorporate various data sources into a cohesive BI architecture.
• Data Governance: Understanding of data governance principles and practices to ensure data quality and consistency.