Director, Engineering Redshift, Analytics Engines

Amazon Redshift is seeking a Director of Engineering to lead the Redshift Engine Team, a global organization spanning the United States and Europe. Amazon Redshift is the most widely used cloud data warehouse, powering SQL analytics on unified data across Redshift Managed Storage and open data lakes for tens of thousands of customers worldwide. The team's vision: build the best SQL analytics engine for humans and agents over any data. This is a rare opportunity to lead at the intersection of analytics, AI, and distributed systems at a massive scale. The team owns the core query processing engine optimization, high-performance execution, catalog, Exabytes of managed storage, and leading-edge autonomics and is innovating across serverless scale-up/scale-out, automated cluster management, AI-driven scaling, zero-ETL integrations, an integrated data lake query engine, and natural-language analytics via Amazon Bedrock Knowledge Bases. As Director, you will own the technical strategy and execution for the engine, shape how AI agents interact with Redshift for intelligent query generation and optimization-aware execution, lead a globally distributed organization, and drive cross-organizational collaboration with partner services including Glue Data Catalog, EMR, Athena, and SageMaker Unified Studio. Key job responsibilities •Define and drive the long-term technical vision for the Redshift query engine as the industry-leading SQL analytics engine for human users and AI agents alike including how autonomous and agentic workloads interact with the engine for intelligent query generation and optimization-aware execution. •Lead and grow a globally distributed engineering organization across the US and Europe, fostering a culture of operational excellence, innovation, and ownership. •Own the architecture and roadmap for query optimization, high-performance execution, scalable catalog, cost-based planning, storage, and self-tuning systems including next-generation solutions for transactional data warehousing and elastic query processing over open-format data at scale. •Drive cross-organizational collaboration across partner services (Glue Data Catalog, EMR, Glue, Athena, SageMaker Unified Studio), building consensus on shared architecture and delivering outcomes that span team charters. •Champion performance and price-performance leadership across serverless, automated cluster management, and real-world customer workloads. •Partner with AI/ML and science teams to advance natural language-to-SQL capabilities and integrate generative AI into the analytics experience. •Build and maintain relationships with strategic customers, incorporating feedback into the engine roadmap. •Establish engineering best practices, mentoring programs, and career development frameworks for a high-performing global team.