Applied Intuition
Staff Data Platform Engineer - Data Engine
Applied Intuition, Sunnyvale, California, United States, 94087
Location
Sunnyvale, California, United States About Applied Intuition
Applied Intuition is the vehicle intelligence company that accelerates the global adoption of safe, AI-driven machines. Founded in 2017 and valued at $15 billion following its Series F funding, Applied Intuition delivers the Vehicle OS, Self-Driving System, and toolchain to help customers build intelligent vehicles and shorten time to market. The company serves the automotive, defense, trucking, construction, mining, and agriculture industries and is headquartered in Mountain View, CA, with offices in multiple locations. Learn more at applied.co. Note: For EpiSci job openings, fully remote work will be considered by exception. 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. What you will do
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 Requirements
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 innovation—building the systems that allow teams to harness massive amounts of real-world and simulated data for developing and validating our stack. You’ll have the autonomy to set the technical direction, the opportunity to solve some of the hardest data engineering problems, and the ability to make a measurable impact on the success of our platform and products. Applied Intuition is an equal opportunity employer. We comply with applicable equal employment opportunity laws and regulations.
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Sunnyvale, California, United States About Applied Intuition
Applied Intuition is the vehicle intelligence company that accelerates the global adoption of safe, AI-driven machines. Founded in 2017 and valued at $15 billion following its Series F funding, Applied Intuition delivers the Vehicle OS, Self-Driving System, and toolchain to help customers build intelligent vehicles and shorten time to market. The company serves the automotive, defense, trucking, construction, mining, and agriculture industries and is headquartered in Mountain View, CA, with offices in multiple locations. Learn more at applied.co. Note: For EpiSci job openings, fully remote work will be considered by exception. 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. What you will do
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 Requirements
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 innovation—building the systems that allow teams to harness massive amounts of real-world and simulated data for developing and validating our stack. You’ll have the autonomy to set the technical direction, the opportunity to solve some of the hardest data engineering problems, and the ability to make a measurable impact on the success of our platform and products. Applied Intuition is an equal opportunity employer. We comply with applicable equal employment opportunity laws and regulations.
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