Director, Data Platform Engineering

Responsibilities

• Build, mentor, and manage a high-performing team of 8-12 data engineering experts
• Define and execute the technical roadmap for the data platform
• Drive innovation in Data Lakehouse and data serving ecosystems
• Ensure reliability, availability, and security of data processing infrastructure
• Partner with data scientists, lab scientists, and product managers to understand data needs
• Represent Lila’s data platform work at external conferences and through technical writing
• Drive innovative, agentic, and low-code solutions for data interfaces and ML/inference workflows

Requirements

• 12+ years of software development experience with a focus on large-scale data processing
• 5+ years of experience leading senior engineers
• Experience building on AWS/GCP primitives (S3, Athena, BigQuery)
• Experience operating data platforms at petabyte scale with sub-second query latency
• Experience managing infrastructure for 100+ concurrent ML training and inference workloads
• Familiarity with LLM/AI-native data patterns including vector stores and embedding pipelines
• Hands-on coding proficiency in Python and modern backend frameworks
• Experience with infrastructure-as-code and Kubernetes
• BS, MS, or Ph.D. in Computer Science or a related field

Preferred Qualifications

• Thought leadership via conference presentations or blog posts
• Experience growing teams focused on open source technologies
• Experience in scientific data management and quality
• Experience building self-service data products where developer experience is a priority

About the Company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously.