Engineering Manager, Data Architecture

ABOUT THE ROLE Anthropic is a rapidly growing company dedicated to creating reliable, interpretable, and steerable AI systems. Our mission is to ensure that AI is safe and beneficial for our users and society as a whole. As the Engineering Manager for Data Architecture, you will lead the team responsible for building our north star implementation of data infrastructure. This team owns the full lifecycle of Anthropic’s most critical data, ranging from customer-facing data like prompts and exchanges to core business data such as logging and financial records. Your mission is to grow this infrastructure into a world-class platform that powers our rapidly expanding business while maintaining the highest standards for AI safety and regulatory compliance. WHAT YOU'LL DO As the Engineering Manager for Data Architecture, you will be responsible for leading a team of world-class data and infrastructure engineers. Your key responsibilities will include: - Building and leading the team, recruiting and mentoring engineers, establishing the team’s technical vision, operational standards, and strategic roadmap. - Driving technical strategy, defining the long-term architecture for Anthropic’s data stack, ensuring it supports high-velocity model training and complex inference workloads across all cloud regions. - Architecting scalable pipelines, leading the design and implementation of robust, automated data pipelines that handle petabyte-scale datasets with high reliability and performance. - Implementing robust governance, building the systems and processes for automated data discovery, lineage tracking, and lifecycle management to ensure high data quality and integrity. - Ensuring data architecture inherently supports global privacy regulations and security requirements through automated controls and privacy-preserving architectures. - Partnering with ML, Product, and Legal teams to unlock the power of data, providing the tools and platforms needed to derive insights without compromising safety. - Standardizing data quality, defining and enforcing SLAs for data availability and accuracy, building internal tools to monitor and maintain the health of the entire data ecosystem. - Evangelizing the data mission, advocating for the importance of modern data architecture as a core component of AI safety, communicating progress and risks to leadership and cross-functional stakeholders. WHAT YOU'LL NEED To be successful in this role, you will need: - Extensive experience managing and scaling engineering teams in high-growth environments, with a focus on data infrastructure or distributed systems. - Deep technical expertise in data modeling, database internals, and large-scale data warehouse/lakehouse architectures. - Proven track record of architecting cloud-native, scalable data platforms that handle multi-cloud deployments and high-throughput data streams. - Strong foundation in data governance principles, including metadata management, data lineage, and automated quality enforcement at scale. - Ability to thrive in high-ambiguity environments, translating broad business goals into specific technical roadmaps and actionable engineering tasks. - Pragmatic approach to engineering, knowing when to build for the future and when to deliver immediate value through iterative improvements. - Excellent communication skills, with the ability to explain complex architectural trade-offs to both technical and non-technical partners. - Comfort with end-to-end ownership and a desire to build a "full-stack" data foundation that serves as the company's single source of truth. WHY REMOTE This is a remote opportunity that allows you to work from anywhere in the world. As a remote employee, you