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As the Technical Lead for Data Pipeline Features within our Model Development Platform, you will play a pivotal role in Wayve's mission to revolutionize autonomous driving. Each day, our teams handle and process multiple petabytes of data collected from our fleet of autonomous vehicles and critical partner integrations. Your technical leadership will directly impact our ability to transform vast amounts of raw data from diverse internal and external sources into structured, actionable insights that power advanced machine learning models and groundbreaking research. By continuously innovating our data ingestion and processing pipelines, you'll help accelerate the development of safer, more efficient autonomous driving technologies, enabling Wayve to maintain its position at the forefront of machine learning innovation.
Job Responsibility:
Define and execute a strategic technical roadmap for enhancing and scaling data pipeline capabilities
Drive innovation in pipeline architecture to support dynamic and evolving use-cases
Lead the design and implementation of advanced data pipeline features for efficient data ingestion, transformation, and distribution
Normalize and unify multiple disparate data sources - including data ingested from external partners - into a consistent and optimized format tailored specifically for AI training and research needs
Collaborate closely with robotics, ML engineering, and research teams to continuously enhance pipeline performance and functionality
Develop robust interfaces and systems to reduce bottlenecks and improve reliability and scalability
Establish and maintain best practices for pipeline reliability, including comprehensive observability, alerting, and monitoring systems
Manage initiatives aimed at minimizing pipeline latency, failure recovery, and ensuring compliance with defined service-level agreements (SLAs)
Engage actively with cross-functional teams (robotics, ML, data governance) to ensure alignment of technical efforts with overall business goals
Foster a culture of transparency, collaboration, and shared ownership across teams
Mentor and develop engineering talent, promoting professional growth and technical excellence within your team
Contribute to the hiring and onboarding processes to expand the capabilities of the data pipeline engineering team
Requirements:
Strong experience (8+ years) in software engineering, specifically focused on developing scalable, complex data pipelines
Proven technical leadership experience in a pipeline engineering or related domain
Expertise in modern data pipeline architectures, including DAG-based orchestration (e.g., Airflow, Flyte)
Solid understanding of data engineering practices, distributed processing frameworks, and pipeline optimization techniques
Excellent communication and collaborative skills, capable of working effectively with interdisciplinary teams
Track record of mentorship and talent development
Bachelor's degree or higher in Computer Science, Engineering, or related technical discipline
Nice to have:
Experience with robotics or autonomous vehicle sensor data processing pipelines
Familiarity with third-party dataset ingestion and transformation
Understanding of compliance and data governance frameworks (e.g., GDPR, TSAX)
Hands-on experience integrating observability and monitoring solutions