Senior Data Modelling Analyst

Overview As Senior Analyst Data Modeling your focus would be to partner with D A Data Foundation team members to create data models for Global projects This would include independently analyzing project data needs identifying data storage and integration needs issues and driving opportunities for data model reuse satisfying project requirements Role will advocate Enterprise Architecture Data Design and D A standards and best practices You will be performing all aspects of Data Modeling working closely with Data Governance Data Engineering and Data Architects teams As a member of the data modeling team you will create data models for very large and complex data applications in public cloud environments directly impacting the design architecture and implementation of PepsiCo s flagship data products around topics like revenue management supply chain manufacturing and logistics The primary responsibilities of this role are to work with data product owners data management owners and data engineering teams to create physical and logical data models with an extensible philosophy to support future unknown use cases with minimal rework You ll be working in a hybrid environment with in-house on-premise data sources as well as cloud and remote systems You will establish data design patterns that will drive flexible scalable and efficient data models to maximize value and reuse Responsibilities Complete conceptual logical and physical data models for any supported platform including SQL Data Warehouse EMR Spark DataBricks Snowflake Azure Synapse or other Cloud data warehousing technologies Governs data design modeling documentation of metadata business definitions of entities and attributes and constructions database objects for baseline and investment funded projects as assigned Provides and or supports data analysis requirements gathering solution development and design reviews for enhancements to or new applications reporting Supports assigned project contractors both on- off-shore orienting new contractors to standards best practices and tools Contributes to project cost estimates working with senior members of team to evaluate the size and complexity of the changes or new development Ensure physical and logical data models are designed with an extensible philosophy to support future unknown use cases with minimal rework Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives maximizes reuse Partner with IT data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper management business and financial policies security local-market regulatory rules consumer privacy by design principles PII management and all linked across fundamental identity foundations Drive collaborative reviews of design code data security features implementation performed by data engineers to drive data product development Assist with data planning sourcing collection profiling and transformation Create Source To Target Mappings for ETL and BI developers Show expertise for data at all levels low-latency relational and unstructured data stores analytical and data lakes data str cleansing Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders Support data lineage and mapping of source system data to canonical data stores for research analysis and productization Qualifications 8 years of overall technology experience that includes at least 4 years of data modeling and systems architecture 3 years of experience with Data Lake Infrastructure Data Warehousing and Data Analytics tools 4 years of experience developing enterprise data models Experience in building solutions in the retail or in the supply chain space Expertise in data modeling tools ER Studio Erwin IDM ARDM models Experience with integration of multi cloud services Azure with on-premises technologies Experience with data profiling and data quality tools like Apache Griffin Deequ and Great Expectations Experience building operating highly available distributed systems of data extraction ingestion and processing of large data sets Experience with at least one MPP database technology such as Redshift Synapse Teradata or SnowFlake Experience with version control systems like Github and deployment CI tools Experience with Azure Data Factory Databricks and Azure Machine learning is a plus Experience of metadata management data lineage and data glossaries is a plus Working knowledge of agile development including DevOps and DataOps concepts Familiarity with business intelligence tools such as PowerBI