About this role
Are you interested in diving deep into data, and engineering the metrics model that drives continuous improvement for Amazon’s pricing systems? Do you have solid problem-solving abilities, metrics-driven decision making and want to solve problems with solutions that will meet the growing worldwide need for Amazon’s products? Then CMT data Platform and Analytics is the team for you. We are part of building one the best, most reliable, and most feature-rich data platform that drives best pricing experience possible and are looking for a good DE Manager. You will lead a team of Data Engineers and Business Intel Engineers as part of the Data Platform and Analytics team in the Competitive Monitoring team aka CMT. We are looking for an experienced and technically skilled individual to lead a team of Data and Business Intelligence Engineers. The ideal candidate will be an analytical, results-oriented, self-motivated, and customer-focused engineering leader who will play a key role in continuous improvement for the critical systems that enable our pricing business. The role will also include surfacing key product metrics as well as building critical data pipelines and analytics tools to improve efficiency and quality of strategic business decisions. The ideal candidate is a motivated self-starter that can work in a fast paced, ambiguous environment with limited supervision and who can quickly absorb the nuances of Amazon's varied pricing programs and processes. Key job responsibilities Delivery of robust, scalable data solutions supporting CMT data infrastructure. - Leadership in data governance and quality standards. - Implementation of GenAI solutions for automated reporting, diagnostic, predictive & prescriptive analytics. - Own technical delivery and team leadership for development and maintenance of scalable ETL/big data pipelines, semantic layers, and dashboard data models. - Collaborate with Product/Program Managers, BI teams, and stakeholders to prioritize work aligned with CMT business goals. - Establish best practices for data engineering, including code reviews, testing, monitoring, and documentation. - Drive team growth through mentoring, coaching, and career development.