We are seeking an experienced Data Scientist with an expert-level in Business Intelligence that focus on designing and implementing Data Vault models.

The ideal candidate will have extensive expertise in architecting and managing enterprise-scale data warehouse solutions to enable data-driven decision-making across the organization.

- Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.

- Proven experience in designing and implementing Data Vault 2.0 architecture.

- Strong proficiency in data modeling, ETL processes, and data warehousing concepts.

- Strong Experience in (SSIS, SSAS,SSRS, and PowerBI).

- Proficient in SQL Server management and data modeling

- Experience with data mining, machine learning, and AI techniques.

- Strong Experience in (Python) programming language for ETL, Data analysis, AI development

- Experience with data visualization tools (Power BI, and Tableau)

- Familiarity with cloud data platforms such as (Azure)

- Strong communication and collaboration abilities.

- Knowledge of data governance and data security best practices.

in Data Vault Modeling, or related data warehousing technologies

1.Data Vault Architecture Design:

- Design and develop Data Vault models that adhere to industry best practices.

- Create hub, link, and satellite tables based on business requirements.

- Ensure scalability, flexibility, and maintainability of the Data Vault architecture.

2.Implementation and Development:

- Implement Data Vault 2.0 methodology for data warehousing projects.

- Develop ETL processes to load data into the Data Vault.

- Optimize ETL workflows for efficiency and performance.

3.Data Integration and Management:

- Integrate data from various sources into the Data Vault.

- Ensure data quality, consistency, and accuracy through validation and testing.

- Manage metadata and documentation for the Data Vault environment.

4.Data Mining and Analysis:

- Perform data mining to identify patterns, correlations, and trends in large datasets.

- Use statistical and machine learning techniques to build predictive models.

- Analyze and interpret complex data to provide actionable insights for business decision-making.

5.Data Visualization:

- Create interactive and visually appealing data visualizations using tools like Power BI.

- Communicate findings and insights through dashboards, reports, and presentations.

6.AI and Machine Learning:

- Develop and implement AI and machine learning models to solve business problems.

- Continuously evaluate and improve model performance.

7.Collaboration and Support:

- Provide guidance and support to team members on Data Vault and data science best practices.

- Collaborate with IT and data governance teams to ensure compliance with data security and privacy regulations.

8.Performance Tuning and Optimization:

- Monitor and optimize the performance of the Data Vault environment.

- Implement strategies for data partitioning, indexing, and query optimization.

- Troubleshoot and resolve issues related to data loading and retrieval.