Entrepreneurship in the territories: is it the right time?
Join us and be a pioneer for a green transport revolution.
Automotive Cells Company (ACC) is one of Europe’s newest and most exciting high-tech companies. Backed by Saft-Total, Stellantis and Mercedes-Benz, ACC is set to power the future of the automotive industry by innovating in battery technology.
We aim to produce sustainable, affordable, high-capacity, longer-life batteries as a cleaner alternative to current energy sources. We have created an R&D center and new state-of-the art facility in Nouvelle Aquitaine, France, and we are building gigafactories in Germany and Italy, in addition to the one already built in Hauts de France.
We need a range of skilled and agile people to bring our vision to life, especially in the areas of industrialization, mechanical design, testing/prototyping and any other function of a new-born company. If you’re looking to take your career further than you imagined, if you’re passionate about creating cleaner transport, we’d like to hear from you.
Our core Values are : Pioneering Spirit, Fast & Agile, Excellence, Greener & Cleaner !
We are also very proud of our 2022 CSR Report : https://www.acc-emotion.com/stories/accs-2022-corporate-sustainability-report
Accelerating sustainable mobility for all.
Data engineers collect, transform and store data using pipelines and storage systems. This involves extracting data from various data source systems, transforming it into the staging area, and loading it into database, data warehouse or datalake systems.
The Data Engineer ensures quantitative and qualitative access to data sources. He/she ensures availability of data and guarantees the quality of its use in-order-to facilitate its exploitation by Data analysts and Data scientists.
His/her scope of intervention is focused on application systems around data management and processing and on Big Data, IoT platforms.
MAIN MISSIONS, OBJECTIVES AND KPIS RELATED
- Analyze and organize raw data
- Build data systems and pipelines
- Evaluate business needs and objectives on data processing
- Conduct report on data pipelines and data consumption
- Prepare data for prescriptive and predictive modeling
- Combine raw information from different sources
- Explore ways to enhance data quality and reliability
- Identify opportunities for data acquisition
- Develop analytical tools and programs
- Collaborate with data scientists and architects on several projects
