Data Engineering Manager

Data Engineering Manager , Retail Business Service Job summary Retail Business Services (RBS) supports Amazon's Retail business growth WW through three core tasks. These are (a) Selection, where RBS sources, creates and enrich ASINs to drive GMS growth; (b) Defect Elimination: where RBS resolves inbound supply chain defects and develops root cause fixes to improve free cash flow and (c) supports operational process for WW Retail teams. Our team of high caliber software developers, applied scientists, data engineers, product managers and Business Intelligence Engineers use rigorous ML and deep learning approaches to ensure that we identify & fix the right catalog defect to ensure the good shopping experience for our customers. As a Data Engineer, you will own and deliver data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective. You strive for simplicity, demonstrate creativity and sound judgement. You deliver data solutions that are customer focused, easy to consume and create business impact. You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics. You have a strategic and long term view on architecting advanced data eco systems. You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications. In this role, you have the opportunity to: Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools. Design, implement and operate large-scale, high-volume, high-performance data for analysis and data science. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture. Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers. Key job responsibilities - Design, implement and operate large-scale, high-volume, high-performance data infrastructure for analysis and data science. - Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture. - Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers. - Lead one of our core engineering teams responsible for building and scaling mission-critical data products that power worldwide operations business decisions. - Drive technical excellence while building and mentoring a high-performing team of data engineers. - Architect scalable solutions that process petabytes of data daily, serving diverse customers retail teams as well as corporate leadership. - Bring strong technical acumen combined with strategic thinking to solve complex problems at scale, while maintaining high operational standards and driving innovation in both traditional analytics and AI/ML domains. - Delivery of robust, scalable data solutions supporting RBS Operations data infrastructure. - Enhancement of real-time analytics capabilities serving RBS Operations leaders. - Leadership in data governance, quality standards, and responsible AI practices across the organization. - 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 Program Managers, BI teams, and stakeholders to prioritize work aligned with RBS business goals. - Establish best practices for data engineering, including code reviews, testing, monitoring, and documentation. - Drive team growth through mentoring, coaching, and career development. - Partner with the GenAI platform team to align data governance, schema standardization, and data contracts where applicable. Preferred qualifications - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with AWS Tools and Technologies (Redshift, S3, EC2) About the team Retail Business Services (RBS) supports Amazon's Retail business growth WW through three core tasks. These are (a) Selection, where RBS sources, creates and enrich ASINs to drive GMS growth; (b) Defect Elimination: where RBS resolves inbound supply chain defects and develops root cause fixes to improve free cash flow and (c) supports operational process for WW Retail teams. Our team of high caliber software developers, applied scientists, data engineers, product managers and Business Intelligence Engineers use ML and deep learning approaches to ensure that we identify & fix the right catalog defect to ensure the good shopping experience for our customers. Basic Qualifications - 5+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL - Experience managing a data or BI team - Experience leading and influencing the data or BI strategy of your team or organization - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience hiring, developing and promoting engineering talent Preferred Qualifications - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with AWS Tools and Technologies (Redshift, S3, EC2) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. #J-18808-Ljbffr