Director, Engineering Redshift, Analytics Engines

Amazon Amazon · Big Tech · East Palo Alto, CA · Software Development

Director of Engineering for Amazon Redshift's core query processing engine, focusing on SQL analytics for humans and AI agents at massive scale. The role involves defining technical strategy, leading a global team, and driving innovation in areas like AI-driven scaling, serverless processing, and natural-language analytics integration.

What you'd actually do

  1. 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.
  2. Lead and grow a globally distributed engineering organization across the US and Europe, fostering a culture of operational excellence, innovation, and ownership.
  3. 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.
  4. 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.
  5. Champion performance and price-performance leadership across serverless, automated cluster management, and real-world customer workloads.

Skills

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • lead at the intersection of analytics, AI, and distributed systems at a massive scale
  • AI agents interact with Redshift
  • natural-language analytics via Amazon Bedrock Knowledge Bases
  • autonomous and agentic workloads interact with the engine
  • natural language-to-SQL capabilities
  • integrate generative AI into the analytics experience
  • Background in AI/ML-powered systems, including large language models, agentic architectures, or natural language interfaces for data systems

Other signals

  • leading a global organization
  • technical strategy and execution
  • cross-organizational collaboration
  • AI agents interact with Redshift
  • natural-language analytics