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Senior Director, Data Platform Engineering

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Lila Sciences, Inc.
Full Time position
Listed on 2026-10-08
Job specializations:
  • IT/Tech
    Data Engineering, Cloud Computing: Infrastructure & Operations, AI Engineer (Applied/Software), Data Science Manager
Salary/Wage Range or Industry Benchmark: 300000 - 390000 USD Yearly USD 300000.00 390000.00 YEAR
Job Description & How to Apply Below

San Francisco, CA USA

Lila is seeking a highly motivated and experienced engineering leader to lead a team responsible for our Lila's product data platform. You will own the data platform and infrastructure end-to-end — architecture, delivery, reliability, and developer/data scientist experience.

Our mission is to deliver Scientific Super Intelligence through a reliable, scalable, and self-service infrastructure for data ingestion, storage, processing, and interaction — enabling AI/ML, product teams, and scientists to build data-intensive applications with confidence and speed. Our platform supports analytical and machine learning workloads across Lila, serving autonomous DBTL cycles, instrument data pipelines, and AI inference workflows.

You will be responsible for building and leading a team of talented engineers, driving technical strategy, and ensuring the scalability and performance of our data management and data serving capabilities of our Data Platform. You will work closely with data scientists, data engineers, lab scientists, and product teams to understand their needs and deliver innovative solutions that leverage the power of cutting edge data processing technologies.

What You'll Be Building

  • Team Leadership:
    Build, mentor, and manage a high-performing team of 30-40 data engineering experts. Evaluate and adopt modern data infrastructure - including real-time streaming (Kafka, Flink), columnar engines (DuckDB, Click House), lake house, and cloud-native object storage architectures;
    Foster a culture of collaboration, innovation, and continuous improvement;
    Provide technical guidance and mentorship to team members, promoting their professional growth;
    Conduct performance reviews, provide feedback, and identify opportunities for training and development;
    Manage team workload, prioritize projects, and ensure timely delivery of high-quality solutions.
  • Technical Strategy and Execution:
    Define and execute the technical roadmap for our data platform, aligning with Lila’s overall data strategy;
    Drive innovation in data Lakehouse and data serving ecosystem exploring new technologies and approaches to improve 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 other Lila systems and services.
  • Stakeholder Management:
    Partner with data scientists, data engineers, lab scientists, product managers, and other stakeholders to understand their data processing needs and requirements;
    Communicate technical concepts and solutions effectively to both technical and non-technical audiences;
    Advocate for best practices in data processing and engineering;
    Manage expectations and ensure alignment across different teams.
  • Engineering Thought Leadership:
    Represent Lila’s data platform work at external conferences;
    Deliver presentations, and write blog posts highlighting Lila’s leadership in big data processing.
  • Scientist and Engineering Productivity:
    Drive innovative, agentic, and low-code solutions to deliver data interfaces - exploration, query, analytics, and ML/inference solutions at scale.

What You’ll Need to Succeed

  • 12+ years of software development experience, with a focus on data processing at scale. 5+ years of experience leading senior engineers.
  • Experience with building on AWS/GCP primitives like S3 + Athena/Big Query, and query engines.
  • Operated data platforms at petabyte scale with sub-second query latency requirements.
  • Experience managing data infrastructure supporting 100+ concurrent ML training and inference workloads.
  • Familiarity with LLM/AI-native data patterns — vector stores, embedding pipelines, pre/mid/post…
Position Requirements
10+ Years work experience
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