Head of Engineering, Inbound Data

What you'll do

• Lead and scale a large engineering organization of over 100 data, ML, and platform engineers.
• Provide strategic technical direction for enterprise-scale lakehouse architecture using Databricks and AWS cloud services.
• Drive the transition to production-grade autonomous AI systems using the Databricks AI stack.
• Establish rigorous engineering standards including SLOs, error budgets, and infrastructure-as-code practices.
• Oversee enterprise semantic modeling and RAG architecture strategies to ensure governed data assets for AI.
• Translate business goals into actionable technical roadmaps in partnership with product and executive leadership.
• Manage hiring, retention, and talent development strategies for high-level engineering roles.

What we're looking for

• Must have 15+ years of engineering experience.
• Must have 5+ years of experience managing and scaling large engineering teams at Director or Head of Engineering level.
• Requires deep expertise in the Databricks Data Intelligence Platform including Unity Catalog, Delta Lake, and MLflow.
• Requires extensive experience architecting enterprise-scale data platforms on AWS using services like S3, Glue, and EMR.
• Must possess technical depth in Apache Iceberg internals and RAG pipeline architecture for production environments.
• Must demonstrate the ability to scale engineering organizations from 20+ to 100+ members while establishing operational SLAs.
• Requires strong communication skills to translate complex technical trade-offs to non-technical stakeholders and executive leadership.
• Preferred qualifications include AWS or Databricks certifications and experience with infrastructure-as-code tools like Terraform.