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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.
We are seeking a talented and motivated Data Quality Engineer to join our team at ACC, a company aiming to become the leader in battery cell manufacturing in Europe for the automotive industry. Producing battery cells at high pace comes with millions of data points created each day and automatic ways to ensure the quality of this data is paramount to the success of ACCs data-driven endeavors.
As a Data Quality Engineer, you will play a critical role in ensuring the accuracy, completeness, and reliability of our data. You will work closely with cross-functional teams in the business lines to enhance data quality according to the data quality dimensions, establish measurement criteria for data quality, and implement automated data quality checks in our data pipelines.
Responsibilities:
- Enhance Data Quality:
o Collaborate with business stakeholders and data engineers to identify key data quality dimensions, such as accuracy, consistency, completeness, timeliness, and reliability.
o Develop a comprehensive understanding of our data sources, transformations, and data flows.
- Establish Measurement Criteria:
o Define clear and measurable data quality metrics for each dimension.
o Implement data profiling and assessment techniques to evaluate data quality.
o Monitor data quality over time and identify areas for improvement.
- Acculturate People:
o Educate and train team members and cross-functional collaborators on data quality best practices.
o Foster a data quality culture within the organization.
o Promote awareness of data quality issues and their impact on business decisions.
- Implement Automated Data Quality Checks:
o Collaborate with data engineers to embed data quality checks into our data pipelines.
o Develop and maintain automated tests to validate data accuracy, consistency, validity, and completeness.
- Continuously Improve Data Quality:
o Participate in root cause analysis of data quality incidents.
o Propose and implement process improvements to enhance data quality.
o Stay informed about industry trends and emerging data quality tools and techniques.
