Director, Engineering Redshift, Analytics Engines

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.

Basic Qualifications

• Bachelor’s degree in Computer Science, Engineering, Math, Statistics or 12+ years equivalent experience
• 10+ years of software engineering experience
• 10+ years leading distributed engineering teams
• Experience with large-scale data systems or database technologies

Preferred Qualifications

• 15+ years of software engineering experience with 5+ years in a senior leadership role (Director or equivalent)
• Deep expertise in database internals, query processing, query optimization, or distributed execution engines
• Track record delivering complex, large-scale infrastructure or platform products at thousands-of-customers scale
• Experience leading globally distributed engineering teams across multiple time zones
• Demonstrated ability to drive cross-organizational alignment and influence technical direction across partner organizations
• Strong understanding of cloud architectures, data analytics patterns, and data lake/open-format ecosystems (Apache Iceberg, Parquet, or similar)
• Experience with query optimizer design, cost-based optimization, high-performance execution engines, or petabyte-scale workload management
• Background in AI/ML-powered systems, including large language models, agentic architectures, or natural language interfaces for data systems
• Track record building and shipping serverless or auto-scaling distributed data systems
• Experience collaborating across diverse analytics or data platform organizations (e.g., data catalog, ETL, query federation, ML platforms)
• Executive presence with excellent written and verbal communication skills, able to influence VP and C-level
• Published research or patents in databases, query processing, or related fields