Lead Data Modeler with SAP

Required Skills & Qualifications:

• Expertise in data modelling tools (ER/Studio, Erwin, IDM/ARDM models, CPG / Manufacturing/Sales/Finance/Supplier/Customer domains )
• Experience with at least one MPP database technology such as Databricks Lakehouse, Redshift, Synapse, Teradata, or Snowflake.
• Experience with version control systems like GitHub and deployment & CI tools.
• Experience of metadata management, data lineage, and data glossaries is a plus.
• Working knowledge of agile development, including DevOps and DataOps concepts.
• Working knowledge of SAP data models, particularly in the context of HANA and S/4HANA, Retails Data like IRI, Nielsen Retail.

 
Key Responsibilities:

• Independently complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, Spark, Data Bricks Delta Lakehouse or other Cloud data warehousing technologies.
• Governs data design/modelling – documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned.
• Develop a deep understanding of the business domains like Customer, Sales, Finance, Supplier, and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse.
• Drive collaborative reviews of data model design, code, data, security features to drive data product development.
• Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; SAP Data Model.
• Develop reusable data models based on cloud-centric, code-first approaches to data management and data mapping.
• Partner with the data stewards team for data discovery and action by business customers and stakeholders.
• Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting.
• Assist with data planning, sourcing, collection, profiling, and transformation.
• Support data lineage and mapping of source system data to canonical data stores.
• Create Source to Target Mappings (STTM) for ETL and BI developers.