Are you curious about how the underlying cloud infrastructure driving Artificial Intelligence (AI) technologies is managed at Amazon? Did you know that inventing frugality-focused systems and tools for AI infrastructure lifecycle management is a collaborative front row seat to an incredible breadth of AI innovation initiatives? In the Alexa Excellence ALICE (AI Logistics for Infrastructure, Cost & Efficiency) team, we drive the infrastructure orchestration, efficiency and cost optimization mechanisms behind products such as Alexa+; striving to be the world's most capable AI personal assistant. We're seeking a Senior Data Engineer who can help us reshape how Amazon develops and deploys large scale AI systems. If the daily invention of AI infrastructure best practices and the opportunity to influence teams/products across internal Amazon and AWS sounds like a fun challenge (spoiler alert, it is!), come join us on the ALICE team! Key job responsibilities As a Senior Data Engineer within the ALICE team, you will demonstrate exceptional technical leadership with comprehensive scope and substantial influence across Amazon's broader technical community. You will be recognized as a technical authority, providing system-wide architectural guidance and design leadership for the team's data architecture and pipeline automation efforts. This role requires deep expertise in data modeling and robust experience with diverse data design approaches, technical architectures, distributed systems and orchestration implementations. You will work autonomously to address ambiguous problem areas in both existing and new data initiatives, taking ownership of architectural decisions that impact upstream and parallel dependencies ranging from legacy systems, enterprise golden sources, and down granular data such as 1-second metrics from CloudWatch. The complexity of this role is exemplified by your ability to analyze, dive deep, make sophisticated architectural trade-off decisions, address scale challenges with big data processing, balance scale and optimization, drive data lake design/evolution, and enable BI self-service tools. As a Senior Data Engineer on the ALICE team, you will work with optimizing operational data storage and processing semi-structured data streams while architecting self-service business intelligence infrastructure for financial analysts, engineering service owners, and leadership personas across organizations including Alexa, AGI (Artificial General Intelligence) and beyond. Data pipeline operations require processing SLAs ranging from annual and monthly mechanisms, down to hourly and near real-time visibility. The quality and consistency requirements are exceptionally high, given a direct dependency for financial reporting across multiple business units. You will ensure the team's continued success through knowledge transfer and system design that enables autonomous operation, making the team stronger through your presence while ensuring it doesn't become dependent on you. A day in the life Examples of responsibilities for this role include: • Architect and deliver exemplary data solutions that are efficient, scalable, maintainable, and aligned with business needs • Lead the architectural vision and strategy for a Unified Data Solution, solving complex big data warehousing problems across hundreds of pipelines and dozens of external dependencies • Tackle complex and hard data problems, breaking down complex challenges into straightforward iterative solutions • Set the standard for data engineering excellence, defining best practices and driving continuous improvement across data pipelines, data models, and analytics processes • Drive the implementation of data engineering best practices, including data discovery, naming conventions, operational excellence, and data security • Collaborate with and guide software engineers and other data engineers to invent, design, and build stable, performant data solutions that provide long-term business value • Communicate technical concepts and tradeoffs effectively to both technical and non-technical audiences, building consensus and alignment • Take ownership of reoccurring pain points/problems, working to resolve root causes that may extend beyond team boundaries and require influence over other teams' decisions • Mentor junior team members, including Data Engineers (DEs) and Business Intelligence Engineers (BIEs), helping them grow their skills and amplify their impact Internal job description ### Basic qualifications - 6+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with MPP databases such as Amazon Redshift - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience building data products incrementally and integrating and managing data sets from multiple sources - Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets - Experience mentoring team members on best practices ### Preferred qualifications - Master's degree - 7+ years of data engineering, database engineering, business intelligence or business analytics experience - Experience providing technical leadership on high-impact cross-fucntional technical project - Experience operating large data warehouses Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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