As we strive to be Earth's most customer-centric company, Amazon has reinvented how hundreds of millions of people shop online – providing customers with the opportunity to find and discover virtually anything they want to buy and providing millions of sellers with a platform for growing successful businesses. We are looking for an exceptional data engineer to help us develop new ways to build trust and loyalty with sellers, a crucial component of our flywheel Sellers’ trust in Amazon is our top priority and in this role, you will be tasked with building that trust over time by building and maintaining the data sources that power all of our decision making. Amazon’s growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems. The successful candidate will be a self-starter, comfortable with ambiguity and be able to create and maintain efficient & automated processes. They know and love working with data engineering tools, can model multidimensional datasets, and can partner effectively with business leaders to build the right data pipelines to answer key business questions. They will build efficient, flexible, extensible, and scalable data models, ETL designs and data integration services. They will also be required to support and manage growth of these data solutions. They are analytical and creative, and don’t quit. This is a role with high visibility to senior leadership and with high opportunity for impact for those willing to roll up their sleeves and dive deep to achieve results. Key job responsibilities In this role, you will work on unifying fragmented data pipelines, building robust data models, and ensuring reliable data lineage across multiple product areas. You will partner closely with software engineers, product managers, and analytics teams to develop data solutions that drive innovation and operational excellence. The ideal candidate brings deep expertise in big data technologies, strong data modeling and problem-solving skills, and a track record of delivering scalable, maintainable data systems. If you’re excited by the challenge of shaping data platforms that support real-world hardware, software, and operations, this is the role for you. A day in the life -Architect and implement scalable, reliable, and secure data pipelines and infrastructure to support analytics, reporting, and business operations. -Design and enforce data modeling standards, data lineage, and governance frameworks that ensure consistency, re-usability, and quality across systems. -Lead design and code reviews, driving engineering best practices across data development, documentation, testing, and monitoring. -Build data platforms and frameworks that support both batch and real-time processing, enabling flexible, efficient analytics at scale. -Implement secure and compliant data solutions that meet internal and external regulatory requirements (e.g., GDPR). -Evaluate and introduce emerging technologies to improve data platform performance, cost efficiency, and scalability. -Collaborate with cross-functional teams to gather data requirements, define solution architectures, and ensure alignment with business needs. -Mentor junior engineers and contribute to team hiring and onboarding ### Basic qualifications - 3+ years of data engineering experience - 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience - 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience - 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience - 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience - 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience - Experience with data modeling, warehousing and building ETL pipelines ### Preferred qualifications - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases) 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.