Data Modeler (Erwin, ER Studios)

Overview Role Overview As a Data Modeler, you will partner with the D&A Data Foundation team to design and implement data models for global projects. This includes analyzing project data needs, identifying storage and integration requirements, and driving opportunities for data model reuse. You will advocate Enterprise Architecture, Data Design standards, and best practices, creating conceptual, logical, and physical data models for large-scale, cloud-based applications impacting PepsiCo’s flagship data products in areas like Revenue Management, Supply Chain, Manufacturing, and Logistics. Responsibilities Key Responsibilities Design conceptual, logical, and physical data models for platforms such as Snowflake, Azure Synapse, SQL Data Warehouse, EMR, Spark, Databricks. Govern data design and modeling, including metadata documentation and database object construction. Collaborate with Data Governance, Data Engineering, and Data Architects to ensure compliance with standards. Prepare Source-to-Target mappings and define data transformation rules for ETL and BI developers. Support data lineage, profiling, and metadata management for enterprise data models. Develop reusable data models with an extensible philosophy to minimize future rework. Partner with IT and business teams to incorporate security, regulatory compliance, and privacy-by-design principles. Drive collaborative reviews of design, code, and data security features. Assist with data planning, sourcing, collection, profiling, and transformation. Advocate data design patterns for scalable and efficient models. Qualifications Must-Have Qualifications 5+ years overall technology experience, including 2+ years in data modeling and systems architecture. 2+ years experience developing Enterprise Data Models. Expertise in data modeling tools: ER/Studio, Erwin, IDM/ARDM. Experience with Snowflake and at least one MPP database technology (Synapse, Teradata, Redshift). 2+ years experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. Strong knowledge of Source-to-Target mapping and canonical model design. Experience with multi-cloud integration (Azure) and on-premises technologies. Basic SQL and/or Python skills. Excellent verbal and written communication skills. Education Bachelor’s degree in Computer Science, Data Management/Analytics, Information Systems, or related discipline. Desirable Skills Knowledge of Azure Data Factory, Databricks, Azure Machine Learning. Familiarity with data quality tools (Apache Griffin, IDQ, Great Expectations, Axon). Azure Basic Level Certification. Experience with metadata management, data lineage, and data glossaries. Knowledge of SAP Master/Transactional Data and CPG industry. Exposure to Machine Learning, GitHub, and CI/CD tools. Working knowledge of Agile, DevOps, and DataOps concepts. Familiarity with BI tools (Power BI).