Global Network Design Data Engineer, End-to-End Supply Chain

Overview This role supports the next generation network design capability, for all Global BUs, Sectors, and ND Global Capability Centers, across the End-to-End Value Chain. The role primarily supports the development, enhancement, and maintenance of the centralized data foundation (e.g. EDF GND Gold) feeding PepsiCo’s SC network models. It helps ensure that model-ready data is accurate, standardized, well-documented, and available for strategic network models (e.g. clean sheet) and related planning models (e.g. capacity/production planning, innovation analysis, asset/investment scenarios). The role may also work with PEP’s data science team to support data preparation, transformation and analysis related to developing data automation and data insights generation related to SC Network Design. Responsibilities Collaborate with business stakeholders to understand data requirements and objectives, to build and maintain the right data solutions supporting network modeling data ingestion and transformation (R),Develop and maintain data pipelines and ETL processes for data extraction, transformation, and loading to make it available in the right structure for the modelers to use (R),Collect, clean, and analyze large datasets using statistical techniques, data mining tools or leveraging upcoming AI/Agentic approaches and frameworks to data engineering (A)/(R),In collaboration with capability and IT teams, help maintain/update the (cloud-based) centralized data layer supporting the global network design modeling capabilities (C) / (R),Identify opportunities for increased the degree of data automation and increase the quality and flexibility of data automation (e.g. user controls) (R),Perform data analysis and establish data quality metrics, monitoring mechanisms, and remediation processes to proactively identify and address data quality issues (A) / (R) Qualifications Degree preferred in IT/IS/CS, Data Analytics, Data Engineering, Data Science or similar Proven experience (3 years) in data management, data engineering, data modeling and/or data science Strong data engineering and database skills in SQL, databricks or similar/popular ETL tools as well as Excel Experience with cloud-based architecture and platforms (Azure, AWS, GCP), data retrieval, querying and data pipeline creation including working with large datasets (Millions+ records, complex joins/querying) Excellent analytical, problem-solving, and decision-making skills Strong communication and interpersonal skills, with the ability to effectively collaborate with stakeholders across geographies & communicate complex findings and concepts to both technical and non-technical audiences Experience with data visualization tools (e.g. Power BI, Tableau) Ability to work independently and manage multiple priorities in a fast-paced environment Process oriented with great documentation skills Advanced level of English, other languages can be nice to have Relations: Building and maintaining trusting relationships across organizational boundaries by modelling integrity, transparency, and authenticity, and being respectful and inclusive of others Additional, Nice to have: Experience with supply chain datasets Experience with or supporting supply chain network design projects and work