Data Modeler / Data Modeller

As a Data Modeller / Data Modeler, you will play a crucial role in leading data architecture efforts across various enterprise domains such as Sales, Procurement, Finance, Logistics, R&D, and Advanced Planning Systems (SAP/Oracle). Your responsibilities will involve designing scalable and reusable data models, building data lake foundations, and collaborating with cross-functional teams to deliver robust end-to-end data solutions. Key Responsibilities: - Work closely with business/product teams to understand processes and translate them into technical specifications. - Design logical and physical data models based on Medallion Architecture, EDW, or Kimball methodologies. - Ensure accurate sourcing of data from true source systems or existing data warehouses. - Create and manage reusable intermediary data models and physical views for reporting and consumption purposes. - Implement Data Governance, Data Quality, and Data Observability practices effectively. - Develop business process maps, user journey maps, and data flow/integration diagrams. - Design integration workflows using APIs, FTP/SFTP, web services, etc. - Provide support for large-scale implementation programs involving multiple projects over extended periods. - Coordinate with data engineers, product owners, data modelers, governance teams, and project stakeholders. Technical Skills: - Minimum 5+ years of experience in data-focused projects such as migration, upgradation, or lakehouse/DWH builds. - Strong expertise in Data Modelling including Logical, Physical, Dimensional, and Vault modeling. - Experience with enterprise data domains such as Sales, Finance, Procurement, Supply Chain, Logistics, R&D. - Proficiency in tools like Erwin or similar data modeling tools. - Deep understanding of OLTP and OLAP systems. - Familiarity with Kimball methodology, Medallion architecture, and modern Data Lakehouse patterns. - Knowledge of Bronze, Silver, and Gold layer architecture in cloud platforms. - Ability to read existing data dictionaries, table structures, and normalize data tables effectively. Cloud, DevOps & Integration Skills: - Familiarity with cloud data platforms like AWS, Azure, GCP, and DevOps/DataOps best practices. - Experience with Agile methodologies and active participation in Scrum ceremonies. - Understanding of end-to-end integration needs and methods including API, FTP, SFTP, and web services. Preferred Experience: - Background in Retail, CPG, or Supply Chain domains is a strong advantage. - Experience with data governance frameworks, quality tools, and metadata management platforms. (Note: The additional details of the company were not present in the provided job description.),