Data Engineering Manager
2 settimane fa
Data Engineering Manager , Retail Business Service Job summary: Retail Business Services (RBS) supports Amazon’s Retail business growth worldwide through three core tasks: (a) Selection, where RBS sources, creates and enriches 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) supporting operational processes for worldwide retail teams. Our team of high‑caliber software developers, applied scientists, data engineers, product managers and business intelligence engineers uses rigorous machine‑learning and deep‑learning approaches to identify and fix the right catalog defects and ensure a great shopping experience for customers. Responsibilities Implement data ingestion routines both real‑time and batch using best practices in data modeling, ETL/ELT processes, leveraging AWS technologies and big‑data tools. Design, implement and operate large‑scale, high‑volume, high‑performance data pipelines for analysis and data science. Gather business and functional requirements and translate them 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. Deliver robust, scalable data solutions supporting RBS Operations data infrastructure. Enhance real‑time analytics capabilities serving RBS Operations leaders. Lead data governance, quality standards, and responsible AI practices across the organization. Implement GenAI solutions for automated reporting, diagnostic, predictive and 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. 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, and EMR. Experience with AWS tools and technologies (Redshift, S3, EC2). Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. 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
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