Staff Data Platform Engineer - Data Engine

About Applied Intuition

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co.

We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.

About the role

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.

At Applied Intuition, you will:

• 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

We're looking for someone who has:

• 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

Nice to have:

• 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

Why Join Us?

You’ll be at the heart of enabling autonomous driving