Data Team Lead

At UVeye, we're 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 over $200M 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 hiring a highly skilled and motivated Data Team Lead. In this role, you will play a pivotal role in leading and strengthening our Data Team, driving innovation, and ensuring the robustness of our data/analytics platforms.

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

• Lead and supervise a diverse team of Data Engineers and Data Analysts and be responsible for guiding team development, conducting performance reviews, and playing a key role in the hiring and training of new team members.
• Take charge of executing analytical projects, leading the development of data analysis, and decision support tools.
• Coordinate closely with the R&D and Sales teams for data integration and alignment, fostering cross-functional collaboration.
• Promote a high-performance culture that encourages success and continuous improvement.
  
  

• 5+ years of experience in data engineering, including team leadership.
• B.Sc. in computer science/information systems engineering.
• Strong SQL expertise, working with various databases (relational and NoSQL) such as MySQL, FireStore, Redis, ElasticSearch.
• Familiarity with data engineering tech stack, including ETL tools (Airflow, Spark, Flink, Kafka, Pubsub).
• Experience with cloud-based data warehouse solutions like BigQuery, Snowflake, Oracle, and proficiency in working with public clouds (AWS/GCP).
• Coding experience with Python
• Experience with dashboard tools like Looker, enhancing data visualization capabilities.