Data Engineer

at  Volvo Cars

ENABLING OUR TRANSFORMATION BY UNLOCKING THE VALUE OF DATA

At Volvo Cars, our strategic direction is clear, shaping the future of mobility with human-centric technologies delivering the freedom to move in a personal, sustainable, and safe way. We are in the middle of a transformation to become a fully electric mobility company by 2030. Our cars will not only become electric, but they will also become defined by the software within them and how we use the data they collect in a responsible and safe way to improve and optimize the consumers’ mobility experience. We are embarking on a journey to build industry and world leading data and analytics capabilities.
We are curious, collaborative, and courageous working together on common goals. Through our words and deeds, we make the difference and bring positive change. We are pioneers in the protection of people and planet.

LET’S GET TO KNOW EACH OTHER!

Are you curious yet? If you want more information about the role and its responsibilities or simply learn a bit more, please reach out to the hiring manager Tobias Romar at tobias.romar@volvocars.com. For questions regarding the recruitment process, please contact malin.hansson.5@volvocars.com.
Please apply for this no later than the 8th of September 2024, enclose your CV and cover letter written in English. Note that due to GDPR we cannot accept applications through e-mail.
Welcome with your application!

AS A DATA ENGINEER YOUR MAIN TASKS AND RESPONSIBILITIES WILL BE TO:

• Design, develop and maintain data products based on data from the finance domain.
• Follow data governance standards and guidelines to ensure data sharing in a trusted and safe way across the organization.
• Treat data as a product – continuously gather feedback, address concerns, and ensure high customer satisfaction throughout the life cycle of the product.
• Collaborate closely with data platform engineers to identify and address platform-related challenges to improve the workflow and developer experience.Iterate on practices and methodologies surrounding the data product development processes.