Applied Intuition-posted 4 months ago
$153,000 - $222,000/Yr
Full-time • Senior
Remote • Mountain View, CA
501-1,000 employees
Publishing Industries

We are looking for a Staff Data Platform Engineer to shape the strategy, architecture, and execution of our next-generation data ecosystem. In this role, you will partner closely with our autonomy stack teams-the 'customers' of our platform-to deeply understand their workflows, pain points, and evolving needs. You will lead the design and development of robust, scalable, and data-intensive distributed systems that power the full lifecycle of autonomous driving data: collection, ingestion, curation, machine learning training, and evaluation. You'll be a key decision-maker in defining best practices, data contracts, and integration patterns across upstream and downstream systems. This is a highly impactful role for someone who thrives at the intersection of technical leadership, system design, and cross-team collaboration, and who wants to elevate the capabilities of our data platform to support cutting-edge ML and autonomy development.

  • Drive Data Platform Strategy - Define the long-term vision and technical roadmap for the data ecosystem, balancing scalability, reliability, cost efficiency, and developer experience
  • Partner with Customers - Engage deeply with autonomy stack teams to gather requirements, uncover pain points, and translate them into platform capabilities
  • Lead Complex Workflow Development - Architect and build end-to-end, large-scale ETL and data workflows for data collection, ingestion, transformation, and delivery
  • Establish Data Contracts - Define and enforce clear SLAs and contracts with upstream data producers and downstream data consumers
  • Set Best Practices - Champion data engineering best practices around governance, schema evolution, lineage, quality, and observability
  • Mentor and Influence - Guide other engineers and teams on designing scalable data systems and making strategic technology choices
  • Collaborate Across Functions - Work with infrastructure, ML platform, autonomy stack, and labeling teams to ensure smooth data flow and ecosystem integration
  • 10+ years of experience in data engineering, distributed systems, or related backend engineering roles
  • Proven track record of architecting and building large-scale, data-intensive, distributed systems
  • Deep experience with complex ETL pipelines, data ingestion frameworks, and data processing engines (e.g., Spark, Flink, Airflow, Flyte, Kafka, etc)
  • Strong understanding of data modeling, partitioning, schema evolution, and metadata management at scale
  • Hands-on experience with cloud object stores (e.g., AWS S3), lakehouse architectures, and data warehouse technologies
  • Ability to drive technical discussions with both engineers and non-technical stakeholders
  • Strong communication and leadership skills, with the ability to influence across teams and functions
  • Experience supporting ML/AI workflows at scale, from raw data ingestion to model training and evaluation
  • Familiarity with data governance, lineage tracking, and observability tools
  • Experience in autonomous systems, robotics, or other high-volume sensor data domains
  • Contributions to open-source data infrastructure projects
  • Comprehensive health, dental, vision, life and disability insurance coverage
  • 401k retirement benefits with employer match
  • Learning and wellness stipends
  • Paid time off
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