Enterprise Data Operations Sr. Analyst
PepsiCo
Overview As a Data Modeler & Functional Data Senior Analyst, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analysing 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, D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architecture 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 Master Data, Finance, Revenue Management, Supply chain, Manufacturing and Logistics. The primary responsibility of this role is 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-premises 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, Data Bricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs Data Design/Modeling – documentation of metadata (business definitions of entities and attributes) and construction of 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 existing, or new, applications/reporting. Lead and Support assigned project contractors (both on & offshore), 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 enhancements or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for proper management of: 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. Analyze/profile source data and identify issues that impact accuracy, completeness, consistency, integrity, timeliness and validity. Create Source to Target Mapping documents including identifying and documenting data transformations. Assume accountability and responsibility for assigned product delivery, be flexible and able to work with ambiguity, changing priorities, tight timelines and critical situations/issues. 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 BA or BS degree required in Data Science/Management/Engineering, Business Analytics, Information Systems, Software Engineering or related Technology Discipline. 8+ years of overall technology experience that includes at least 4+ years of Data Modeling and Systems Architecture/Integration. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing Enterprise Data Models. 3+ years of Functional experience with SAP Master Data Governance (MDG) including use of T-Codes to create/update records and query tables. Extensive knowledge of all core Master Data tables, Reference Tables, IDoc structures. 3+ years of experience with Customer & Supplier Master Data. Strong SQL skills with ability to understand and write complex queries. Strong understanding of Data Life cycle, Integration and Master Data Management principles. Excellent verbal and written communication and collaboration skills. Strong Excel skills for data analysis and manipulation. Strong analytical and problem-solving skills. 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. Working knowledge of agile development, including Dev Ops and Data Ops concepts. Experience mapping disparate data sources into a common canonical model. Differentiating Competencies Experience with metadata management, data lineage and data glossaries. Experience with Azure Data Factory, Databricks and Azure Machine learning. Familiarity with business intelligence tools (such as Power BI). CPG industry experience. Experience with Material, Location, Finance, Supply Chain, Logistics, Manufacturing & Revenue Management Data.
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