We are seeking a highly skilled and hands-on Data Engineer III or Senior Data Engineer (Analytics Focus) to design, build, and support enterprise analytics solutions, data models, and reporting experiences that enable data-driven decision making across the organization. This is first and foremost an analytics-focused data engineering role. The ideal candidate has strong expertise in data modeling, analytics engineering, Microsoft Fabric, Databricks, Python development, and modern business intelligence solutions. The successful candidate will be responsible for developing and maintaining enterprise data models, semantic layers, reporting datasets, and analytical applications that support operational reporting, executive dashboards, self-service analytics, and advanced business insights.  This role sits within the engineering discipline and works closely with product teams, platform engineers, architects, and business stakeholders to ensure enterprise reporting and analytics solutions are built on reliable data foundations, aligned with business objectives, and capable of scaling with future needs. This position supports the Americas geography under the IS organization and contributes to initiatives that enhance operations across 70+ offices in multiple countries. A Successful Data Engineer III / Senior Data Engineer: Building enterprise analytics solutions using Microsoft Fabric, Databricks, SQL, Python, and Power BI.  Design and develop semantic models and reporting datasets that support self-service analytics and executive reporting.  Creating intuitive, user-focused reporting experiences that improve data visibility and decision making.  Translating complex business requirements into scalable analytical solutions.  Establishing data quality standards and validation processes that ensure trust in reporting.  Optimizing analytics solutions for performance, usability, and maintainability.  Leading data design discussions and influencing data architecture and modeling best practices.  Collaborating effectively with business stakeholders to define KPIs, metrics, and reporting requirements.  Mentoring team members and promoting engineering excellence through collaboration, design reviews, and knowledge sharing. Major Duties and Responsibilities Technical Depth and Delivery Lead the development of enterprise data models, semantic layers, analytics solutions, and reporting datasets that provide trusted and scalable business insights.  Establish and promote best practices for data quality, testing, automation, observability, version control, CI/CD and operational excellence across analytics solutions. Provide technical leadership through code reviews, solution design guidance, and mentorship of engineers on performance, maintainability, scalability, and solution quality. Architectural Scale Design scalable data models, reporting architecture, and analytics solutions that support current and future business needs.  Partner with architects and engineering leaders to ensure solutions align with enterprise engineering principles and standards for metric governance, semantic modeling, and analytics solutions. Evaluates scale on solution footprint  Team Collaboration Scale Collaborate with engineering, architecture, product, and business teams to deliver high-impact analytics capabilities.  Serve as a trusted technical partner in translating business requirements into actionable data and reporting solutions.  Mentor team members through coaching, knowledge sharing, and constructive technical feedback.  Influence and Advocacy Advocate for analytics engineering best practices, standardized metrics, and data-driven decision making across teams and department.  Communicate technical concepts, data insights, and solution recommendations to both technical and non-technical audiences.  Influence reporting, data modeling, and analytics strategies through active participation in architectural and business discussions.  Scope of Vision Develop and communicate a strategic vision for analytics, reporting, and data visibility solutions aligned to business priorities.  Identify opportunities to improve organizational visibility, operational performance, and analytical capabilities by balancing immediate delivery needs with long-term sustainability, scalability, and maintainability of analytics solutions. Scale of Business Understanding and Impact Develop a deep domain knowledge of logistic operations, understanding business processes and key performance metrics to guide solution design.  Ensure analytics solutions deliver actionable insights that support measurable business outcomes and operational improvements.  Continuously improve the usability, accessibility, and effectiveness of data products, reports, and analytical experiences for end users.