Staff Engineer, Data Platform
AI summary of the role
Lila Sciences is building an autonomous AI platform for scientific discovery.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Design and evolve core data infrastructure for scientific and ML workflows
- Build reliable ingestion pipelines from laboratory instruments, public datasets, and research literature
- Operate and extend workflow orchestration systems for multi-step scientific pipelines
- Define data models, schema evolution practices, and data contracts for consistency and durability
What you’ll bring
- 8+ years as a software or data engineer focused on data infrastructure
- Designed and shipped data platform components from the ground up (ingestion, storage, orchestration)
- Fluent in Python and SQL with production-quality code
- Production experience with relational and NoSQL databases, schema design, and query optimization at scale
Technologies
Python · SQL · AWS · Kubernetes · Iceberg · Delta Lake · Hudi · Flyte · Airflow · Dagster
About Lila Sciences
Autonomous AI platform that executes the scientific method end-to-end—from hypothesis generation to experimental execution—for biotech, materials, and chemical R&D.
Series A
Source and classification
Internal deployment & tooling · Evidence for this classification:
Your Impact at LILA Lila Sciences is building the software platform that makes automated scientific discovery possible. At the heart of that platform is data: raw outputs from laboratory instruments, experimental model results, curated public datasets, and the scientific literature that contextualizes all of it. The data platform team is responsible for the infrastructure that moves, stores, transforms, and surfaces this data across the organization. We are looking for a Staff Engineer to set the technical direction for our core data infrastructure: ingestion frameworks, storage architecture, orchestration patterns, and the interfaces that let scientists and ML researchers work with data reliably at scale. You will work closely with software engineers, machine learning researchers, and lab scientists to understand requirements and translate them into durable platform capabilities.
More from the job description
Your Impact at LILA Lila Sciences is building the software platform that makes automated scientific discovery possible. At the heart of that platform is data: raw outputs from laboratory instruments, experimental model results, curated public datasets, and the scientific literature that contextualizes all of it. The data platform team is responsible for the infrastructure that moves, stores, transforms, and surfaces this data across the organization. We are looking for a Staff Engineer to set the technical direction for our core data infrastructure: ingestion frameworks, storage architecture, orchestration patterns, and the interfaces that let scientists and ML researchers work with data reliably at scale. You will work closely with software engineers, machine learning researchers, and lab scientists to understand requirements and translate them into durable platform capabilities. This is a role for engineers who care deeply about how data systems are designed. You will establish the architectural patterns and engineering standards the broader team builds on, mentor engineers across the data platform group, and make technical decisions that compound over time. What You'll Be Building Data Platform Architecture: Design and evolve the core data infrastructure that ingests, stores, and serves data across scientific and ML workflows. Make principled build-vs-buy decisions and [... source excerpt omitted ...] cientific and platform data assets. Cross-Functional Technical Leadership: Partner with ML researchers, lab scientists, and product engineers to translate scientific and research requirements into platform capabilities. Drive alignment on data standards and integration patterns across teams. Engineering Standards and Mentorship: Establish coding, review, and design standards for the data platform team. Mentor engineers, lead design reviews, and raise the technical bar across the group. What You’ll Need to Succeed Bachelor's or Master's degree in Computer Science, Engineering, or a related field, and 8+ years as a software or data engineer with a focus on building and operating da [... source excerpt omitted ...] igned and shipped data platform components from the ground up, including ingestion frameworks, storage abstractions, and orchestration systems. Fluent in Python and SQL and writes production-quality code. Production experience with relational and NoSQL databases, schema design, query optimization, and operational concerns at scale. Comfortable working across structured, semi-structured, and unstructured data. Proven track record of working cross-functionally with scientists, ML researchers, and engineers. Able to translate domain requirements into platform decisions and explain technical trade-offs to diverse audiences. Experience with cloud infrastructure and containerized depl
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