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Director of Data Platform Engineering

Lila SciencesSan Francisco, CA USA
On-site Full-time $232K/yr - $304K/yr

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Experience Level

Senior Level Manager

Qualifications

To excel in this role, candidates should possess: Proven experience in leading data engineering teams and managing complex data platforms. Strong expertise in data infrastructure technologies, including streaming, databases, and cloud solutions. Excellent problem-solving skills and a passion for innovation in data processing. Exceptional communication skills to articulate technical concepts clearly to diverse audiences. A collaborative mindset with the ability to work effectively across teams.

About the job

Your Impact at Lila

Lila Sciences is on the lookout for a dynamic and seasoned engineering leader to spearhead our product data platform team. You will take full ownership of the data platform and its underlying infrastructure — encompassing architecture, delivery, reliability, and the user experience for developers and data scientists.

Our mission is to unleash Scientific Super Intelligence by providing a dependable, scalable, and self-service infrastructure for data ingestion, storage, processing, and interaction. This empowers AI/ML, product teams, and scientists to efficiently create data-driven applications with speed and confidence. Our platform is designed to handle analytical and machine learning workloads across Lila, facilitating autonomous DBTL cycles, instrument data pipelines, and AI inference workflows.

As the Director, you will build and lead a team of skilled engineers, drive technical strategy, and ensure the scalability and performance of our data management and serving capabilities. You will collaborate closely with data scientists, data engineers, lab scientists, and product teams to gather insights into their needs and deliver innovative solutions that harness cutting-edge data processing technologies.

What You'll Be Building

  • Team Leadership: Develop, mentor, and oversee a high-performing team of 8-12 data engineering experts. Assess and implement modern data infrastructure - incorporating real-time streaming (Kafka, Flink), columnar engines (DuckDB, ClickHouse), lake house architecture, and cloud-native object storage. Cultivate a collaborative, innovative culture focused on continuous improvement. Provide technical mentorship to team members, supporting their professional development; conduct performance reviews, offer feedback, and identify training opportunities. Manage team workloads, prioritize projects, and ensure the timely delivery of high-quality solutions.
  • Technical Strategy and Execution: Define and implement the technical roadmap for our data platform, aligning with Lila’s overarching data strategy. Foster innovation within the data Lakehouse and data serving ecosystem by exploring new technologies and methodologies to enhance usability, performance, scalability, and efficiency. Ensure the reliability, availability, and security of our data processing infrastructure. Collaborate with other engineering teams to integrate our data processing technologies with additional Lila systems and services.
  • Stakeholder Management: Collaborate with data scientists, data engineers, lab scientists, product managers, and other stakeholders to understand their data processing needs and requirements. Effectively communicate technical concepts and solutions to both technical and non-technical audiences. Advocate for best practices in data processing and engineering.

About Lila Sciences

Lila Sciences is dedicated to transforming scientific exploration through advanced data solutions. Our innovative approach empowers teams to leverage data for breakthroughs in research and product development. Join us in our mission to deliver the next generation of scientific intelligence.

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