Description Amazon's Global Logistics team is seeking an experienced Business Intelligence Engineer who will help build the next generation of analytical solutions & data automations for Global Logistics Services org. Global Logistics Services is a team of highly experienced logistics professionals, carrier specialists, program managers and tech professionals focused on improving the speed and reliability of Amazon’s cross-border logistics capabilities. Leveraging the capabilities of world-class logistics providers and internal Amazon supply chain solutions, Global Logistics increases selection and lowers cost for our customers. You will be part of the central Business Intelligence (BI) team which supports Global Logistics Services by providing the business with the right data, information and analytics in a scalable manner, enabling stakeholders (e.g. logistics coordinators, program managers, leaders) to make timely data-driven decisions to optimize speed, cost and reliability of global import shipments. Your colleagues and key stakeholders will be based mainly in different parts of the world. The ideal candidate will have experience/knowledge in working with large datasets and enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. They are an expert in leveraging and building GenAI tools, data pipelines and has hands-on knowledge/experience in managing structured databases/data warehouses (e.g. Amazon Redshift) and other AWS technologies (e.g. S3, Lambda). They passionately partner with customers, stakeholders and other tech teams (e.g. data engineering) to identify strategic opportunities in the field of Artificial Intelligence, data analytics & engineering. They are a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail) and enjoys working in a fast-paced team that continuously learns and evolves on a day to day basis. They will also be a key influencer within the team, providing input on priorities, technical designs, and technology decisions with a focus on scalable, maintainable and efficient systems and processes. Key job responsibilities - Design, development and ongoing operations of scalable, performant data tables (Redshift), data pipelines, reports and dashboards. - Development of moderately to highly complex data processing jobs using appropriate technologies (e.g. SQL, Python, Spark, AWS Lambda, etc.). - Adept at leveraging and building AI tools - Collaborating with stakeholders to understand business domains, requirements, and expectations. Additionally, working with owners of data source systems to understand capabilities/limitations and to address data issues. - Deliver moderately complex data analyses to facilitate business & technical decision making, collaborating with other tech teams (e.g. Data Engineering) as needed. - Actively manage the timeline and deliverables of projects, anticipate risks and resolve issues. - Adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation. - Provide input on technical designs and technology decisions within the team, with a focus on scalable, maintainable and efficient systems and processes. About the team Global Logistics Analytics (GLA) team is dedicated to supporting the Global Logistics Services (GLS) business by delivering trusted, easily accessible, and actionable data and insights. Established in Q3’21 within the EU operations, GLA currently manages 45+ reporting and analytical products for GLS Ops across regions. Our mission is to help drive business decisions that enhance speed, cost-efficiency, and reliability of global import shipments. Basic Qualifications - Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business - Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc. - Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets - Experience with data visualization using Tableau, Quicksight, or similar tools - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling - Experience using/building AI tools for analytics use cases Preferred Qualifications - Experience working as a BIE in a technology company - Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift - Has AWS Cloud Practitioner or higher certifications. - Has experience building ML models such as time-series, classification models, regression or predictive analysis, etc. Amazon is an equal opportunities employer. 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