Business Intelligence Engineer, Supply Chain Data Science (Xico)

Lead the design and delivery of AI-native data architectures that power GenAI-enabled decision support across Mexico Supply Chain operations.

Define logical data models, build scalable business intelligence solutions natively integrated with AI agents, and drive efficiency gains for Program Managers, Product Managers, and Supply Chain Managers through self-service analytics and automated insights.

Own cloud infrastructure resource strategy and technical budget optimization for the Mexico Supply Chain BI team while architecting extensible data pipelines that reduce manual preparation effort and enable coherent BI product adoption across North America, Europe, Emerging Countries and Cross-border Fulfillment, and Rest of World.

Key Job Responsibilities

• Data Architecture & AI-Native Solutions: Define logical data models and data architecture for the Mexico Supply Chain team, ensuring solutions are extensible, scalable, and AI-native.
• Architect data pipelines and structures optimized for GenAI agent consumption, enabling self-service analytics and reducing manual data preparation effort.
• Design AI-native data integration systems and algorithms that ensure coherent adoption of BI products across Mexico, central teams, and other geographies (North America, Europe, Emerging Countries and Cross-border Fulfillment, Rest of World).
• Establish data governance standards and documentation that support non-technical stakeholders in leveraging AI-powered analytics and decision support tools.
• Technical Leadership & Cross-Functional Coordination: Coordinate cross‑functional technical teams (Business Intelligence Engineers, Data Engineers, Scientists) to deliver country-level strategic goals.
• Engage directly with Mexico planning and operations leadership to assess requirements, track project delivery, and influence data-driven decision making.
• Collaborate with cross‑functional technical teams across geographies (North America, Europe, Emerging Countries and Cross-border Fulfillment, Rest of World) to ensure tool parity, coordinate deployments, and manage productization handovers.
• Build consensus across technical and non-technical stakeholders on data architecture approaches, AI integration strategies, and solution designs.
• Budget & Resource Management: Own cloud infrastructure and technical resource budget planning, strategy, and optimization for the Mexico Supply Chain BI team.
• Drive cost reduction initiatives while ensuring infrastructure supports AI-ready data architectures.
• Partner with Product Managers to define business requirements, product designs, and documents that incorporate GenAI capabilities and data consumption patterns.
• Manage team cost-out metrics and demonstrate financial accountability through accurate budget forecasting and reporting to finance stakeholders.
• Complex Problem Solving: Tackle complex data problems across the supply chain lifecycle, from short-term operational needs to long-term strategic planning.
• Design logical data models, prototypes, and scalable data pipelines for forecasting, simulation, and predictive analytics.
• Solutions are extensible, maintainable, and architected for AI-native consumption, enabling GenAI agents to access structured data with mínimal preprocessing.
• Team Development: Actively mentor and develop Business Intelligence Engineer II team members, perform technical assessments for promotions, and contribute to the professional development of the broader BI engineering community.

Basic Qualifications

• Experience programming to extract, transform and clean large (multi‑TB) data sets.
• 1+ years of integration, testing and automation experience, or AWS Professional level certification.
• Experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, or information retrieval.
• 3+ years of data engineering, database engineering, business intelligence or business analytics experience.
• 3+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience.
• Experience building data pipelines or automated ETL processes.
• 3+ years of cloud architecture and solution implementation experience, or AWS Associate level certification.
• Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage.
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.
• Experience mentoring or training the engineering community on complex technical issues.

Preferred Qualifications

• Experience working directly with business stakeholders to translate between data and business needs.
• Experience managing, analyzing and communicating results to senior leadership.
• AWS Professional level certification, or experience in performance optimization and cost management for cloud environments.
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