Data Operations Lead

About Stack: Stack is developing revolutionary AI and advanced autonomous systems designed to enhance safety, reliability, and efficiency of modern operations. Stack's autonomous technology incorporates cutting-edge advancements in artificial intelligence, robotics, machine learning, and cloud technologies, empowering us to create innovative solutions that address the needs and challenges of the dynamic trucking transportation industry. With decades of experience creating and deploying real world systems for demanding environments, the Stack team is dedicated to developing an autonomous solution ecosystem tailored to the trucking industry's unique demands. If you are an Internal Candidate, please apply via our Internal Job Board . About the Role: The Data Operations organization is responsible for ensuring a high throughput of quality data critical to the development and validation of our Self Driving System. As the Data Operations Lead, you will oversee and scale multiple pivotal functional areas, including Mapping Operations, Labeling Operations, Triage Operations, and other future data centric operational teams as the company expands. In this leadership role, you will manage metrics driven internal teams as well as external vendors responsible for delivering high-fidelity maps, annotated sensor data, and accurate triage analysis. You will partner closely with Product, Autonomy, and Systems Engineering teams to identify and define cross-functional requirements, ensuring efficient tooling and automation to streamline workflows across all your verticals. This is a highly impactful leadership role essential to the ongoing development, validation, and deployment of our Autonomy System, requiring broad collaboration across Stack. Responsibilities: Lead and Scale : Direct the Data Operations organization within Product Development, encompassing Mapping, Labeling, Triage, and future operational teams. Collaborate on Strategy : Partner with key stakeholders across the organization to define, standardize, and continually refine data ontologies, operator policies, and data specifications. Optimize Workflows : Ensure efficient workflows and policies are established to deliver a high volume of quality data (labels, maps, and triage annotations) that meet complex customer needs on a continuous basis. Manage Vendor Relationships : Oversee all aspects of strategic vendor relationships and partner organizations responsible for ground truth labeling, map generation, and operational tasks, including contract negotiation, budget management, training, and policy adherence. Drive Automation : Partner with internal tooling and infrastructure teams to define requirements for next-generation tooling and automation to reduce manual operational overhead. Data Driven Improvement : Utilize data analytics to identify opportunities for continuous improvement in operational workflows, throughput, and quality control processes. Qualifications: …