Amazon Devices is looking for a Data Engineer to work with big data related to Amazon's expanding portfolio of Devices, from FireTV, to Ring, to the Echo/Alexa family of products. You will be joining the International Devices Data Services (IDDS) team, whose mission is to empower business stakeholders with data products in support of sales & marketing operations to enable data-driven decisions, and will be supporting international BI teams across Europe, Brazil, India, and Japan with data infrastructure. As a Data Engineer, you drive data engineering initiatives and build solutions that are stable, scalable, secure, and cost-effective, using AWS tools and services. You balance inventiveness with simplicity, while demonstrating sound judgement. Beyond traditional data engineering, this role sits at the center of the team's AI adoption. Our AWS environment is not only a reporting backbone — it is a deployment platform that allows our team to take locally developed AI proofs of concept and scale them into production solutions. You will help translate these proofs of concept into production-grade solutions and ensure our platform scales to meet the demands of new AI-powered workstreams. This agility is critical at a moment when speed of AI adoption directly translates to business impact. You will be working in one of the world's largest and most complex data warehouse environments, supporting multiple high-visibility, business-facing workstreams requiring complex data pipeline integration. You are an expert in the architecture of data warehousing solutions using multiple technologies, with experience using AWS services. You excel in the design, creation, management, and business use of very large datasets. You have excellent business and communication skills, working with engineers and analysts to build data sets that support downstream analytical needs. Industry experience in data engineering or a related field (e.g., software engineer, business intelligence) with a track record of manipulating, processing, and extracting value from large datasets, is required. Key job responsibilities - Own and operate the data engineering infrastructure used by analysts and engineers across partner teams and international locales. - Design, implement, and operate large-scale, high-volume, high-performance data sets for use by business intelligence engineers and analysts. - Implement data pipelines using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools. - Collaborate with engineers to adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation. - Help continually improve ongoing data infrastructure processes, automating or simplifying self-service modeling and production support for stakeholders. - Understand data governance and compliance mandates, and work with engineers to implement appropriate controls and drive migration campaigns. - Collaborate with BI stakeholders as a subject matter expert and leader of data infrastructure support. - Champion best practices in data acquisition, identifying data needs, driving data quality improvement projects, and raising the technical bar for the team. - Be a self-starter who is comfortable with ambiguity, has attention to detail, and can work in a fast-paced, collaborative, and international environment. About the team International Devices Data Services’ (IDDS) mission is to enable data-driven decision making by providing data, reporting, and actionable insights to Amazon Devices. Our team has a diverse mix of talent, combining Business Intelligence Engineers, Data Engineers, and a Technical Program Manager into a single team which allows us to own data-driven solutions end-to-end. We have technical skills across a wide range of technologies and AWS services to deploy solutions at scale. ### Basic qualifications - 3+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets - Ability to build data pipelines that transform raw data into structured datasets ready for AI model consumption & use - Strong working knowledge of/experience with large language models (LLMs), including prompt engineering, model selection, and instructions fine-tuning to optimize model performance for analysis against large datasets. - Experience with scripting and API integration with AWS AI services (or similar) such as Amazon Bedrock and SageMaker to embed AI capabilities into production workflows. ### Preferred qualifications - 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. 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