Senior Data Scientist - Data Modelling

• Design and develop data models in consultation with Data Architects and Solution Architects.
• Develop and maintain Logical Data Models and translate logical models into appropriate physical data models.
• Gather, analyze, and document data requirements from business stakeholders.
• Work with stakeholders to understand business requirements and translate them into effective data modelling solutions.
• Make informed technical decisions and drive progress in situations where information or requirements may be incomplete.
• Apply Data Vault 2.0 principles to design robust and scalable data models.
• Develop and work with SQL and Oracle SQL for data modelling and data-related solutions.
• Contribute to data integration and data modelling activities within SAP-related projects.
• Work with business data entities such as customer and stock within retail-related environments.
• Collaborate with Data Architects, Solution Architects, business stakeholders, and technical teams to ensure alignment between business requirements and data architecture.
• Follow data modelling standards, best practices, and established architecture principles.
• Contribute to continuous improvement of data modelling approaches, processes, and solutions., * Design high-quality logical and physical data models based on business and technical requirements.
• Translate complex business requirements into clear and scalable data models.
• Explain and communicate data modelling concepts effectively to both technical and non-technical stakeholders.
• Gather requirements from business stakeholders and identify the underlying data needs.
• Work effectively with incomplete information and make sound technical decisions.
• Apply Data Vault 2.0 concepts and principles in data modelling.
• Write and understand complex SQL and Oracle SQL queries and data structures.
• Collaborate effectively with Data Architects, Solution Architects, developers, and business teams.
• Analyze existing data structures and identify opportunities for improvement.
• Ensure data models align with business requirements, architecture standards, and technical constraints.
• Work independently while taking ownership of data modelling deliverables.
• Communicate clearly and effectively in a stakeholder-facing environment.
• Adapt to changing requirements and work effectively in a dynamic project environment.

What we bring to the table:

• The opportunity to work on complex enterprise data modelling and data architecture initiatives.
• Exposure to Logical and Physical Data Modelling and Data Vault 2.0 methodologies.
• Opportunities to work with Oracle SQL and modern data technologies.
• Collaboration with Data Architects, Solution Architects, business stakeholders, and technical teams.
• Exposure to data integration and modelling activities within SAP-related projects.
• Opportunities to work with modern data technologies such as dbt and BigQuery.
• A collaborative environment focused on solving complex data challenges and delivering scalable data solutions.
• Opportunities to contribute to data architecture, modelling standards, and continuous improvement.

• 8-10 years of overall professional experience in data science, data modelling, data architecture, or closely related data disciplines.
• Extensive hands-on experience with data modelling.
• Strong experience developing and working with Logical Data Models.
• Proven ability to translate between logical and physical data models.
• Strong knowledge of Data Vault 2.0.
• Strong experience with SQL, particularly Oracle SQL.
• Strong understanding of data concepts, data structures, and data modelling principles.
• Experience gathering and translating business requirements into data models and technical solutions.
• Strong communication and stakeholder management skills.
• Experience working closely with Data Architects and Solution Architects.
• Experience making technical decisions and progressing work in situations involving incomplete or evolving information.
• Experience with data integration and data modelling in SAP-related projects is advantageous.
• Knowledge of retail data entities, particularly customer and stock data, is beneficial.
• Experience with dbt, BigQuery, and GitHub is advantageous.