Senior Data Engineer

At UVeye, we are on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, representing the pinnacle of machine learning, GenAI, and computer vision within the automotive sector.

With close to $400 million in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity and encourages teamwork. Our drive for innovation and pursuit of excellence are deeply embedded in our vibrant company culture, ensuring that each individual's efforts are recognized and valued as we unite to build a safer automotive world.

We are looking for an experienced Senior Data Engineer to join our Data team.

In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.

A day in the life and how you’ll make an impact:

• Design and develop high-performance data pipelines to support diverse business needs.
• Implement robust data quality checks, monitoring mechanisms, and data governance policies to maintain data integrity and security, troubleshooting and resolving any data-related issues efficiently.
• Continuously improve our data analytics platforms, optimizing system performance while ensuring a robust and reliable data infrastructure.
• Oversee the entire data lifecycle, from infrastructure setup and data acquisition to detailed analysis and automated reporting, driving business growth through data-driven insights.
  
  

• 5+ years of experience in data engineering (preferably in a startup), designing and implementing scalable, analytics-ready data models and cloud data warehouses (e.g., BigQuery, Snowflake).
• B.Sc. in Computer Science / Engineering or equivalent.
• Extensive experience with modern data orchestration and transformation frameworks (e.g., Airflow, DBT).
• Strong knowledge of databases, including SQL (schema design, query optimization) and NoSQL, with a solid understanding of their use cases.
• Strong familiarity with cloud data services (e.g., AWS, GCP) and streaming platforms (e.g., Kafka, Pub/Sub).
• Fluent in SQL and Python with a backend orientation (services, APIs, CI/CD).
• Ability to communicate and explain complex ideas simply.
• Experience with, or a strong desire to learn, the practical value of AI and automation tools for improving efficiency.
• Passionate about technology, proactively identifying and implementing tools to enhance development velocity and maintain high standards.
• Adaptable and resilient in dynamic, fast-paced environments, consistently delivering results with a strong can-do attitude.