OverviewData Engineer II, Managed Operations Engineering & Data Science (MOEDS) — AWSAmazon Web Services (AWS) is the world leader in providing a highly reliable, scalable cloud infrastructure. This role supports MOEDS, a group focused on reducing operational load and toil through long-term engineering projects that improve availability, reliability, latency, performance, and efficiency for AWS Regions. This position requires that the candidate selected be a U.S. Citizen.Key responsibilitiesCollaboration and Product Development: Interact with business and software teams to understand their requirements and operational processes to inform system designData Modeling and Architecture: Develop robust data models and architectures to support data-driven initiatives, ensuring data quality, consistency, and accessibilityData Pipeline Development: Design, build, and maintain scalable and reliable data pipelines to ingest, transform, and load data into a unified data platformScalability and Performance: Design and implement scalable data solutions that handle increasing data volumes and support high-performance data access and queryingDocumentation & Continuous Improvement: Create, enhance, and maintain technical documentationA day in the lifeWork in a state-of-the-art innovation lab within AWS, pushing the boundaries of cloud management through long-term engineering initiatives. Join Data Science & Data Engineering teams in leveraging advanced analytics, machine learning, and artificial intelligence to inform high-impact investment decisions and reduce operational toil. The Data Engineering team focuses on democratizing data and delivering highly scalable, highly available solutions for customers.What we offerAdvanced tech stack including big data technologies (e.g., AWS Glue, Apache Airflow), AI/ML, and cloud-native tools (CloudFormation)Opportunity to work on projects that impact millions of AWS customersCollaborative environment with leaders in cloud computing and data scienceOpportunity to shape the future of cloud operations and set industry standardsAbout the team & AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We foster a culture of inclusion and continuous learning. AWS Utility Computing (UC) provides innovations across compute, database, storage, IoT, platform, and productivity apps, including security-focused solutions.Inclusive Team Culture: Our employee-led affinity groups foster inclusion and ongoing learning experiences. Work/Life Balance: We value flexibility and support in the workplace and at home. Mentorship & Career Growth: We provide knowledge-sharing, mentorship, and resources to help you develop professionally. Diverse Experiences: We encourage applicants with non-traditional backgrounds to apply.BASIC QUALIFICATIONS3+ years of data engineering experienceExperience with data modeling, warehousing, and building ETL pipelinesKnowledge of distributed systems as it pertains to data storage and computingExperience in at least one modern scripting or programming language (Python, Java, Scala, or NodeJS)PREFERRED QUALIFICATIONS5+ years of data engineering experienceExperience building/operating highly available, distributed data extraction, ingestion, and processing systemsExperience with non-relational databases/data stores (object storage, document/key-value stores, graph databases, column-family databases)Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles/permissionsAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require accommodations during the application or hiring process, including interview or onboarding support, please visit amazon.jobs/accommodations for more information.
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