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Job Description

Northvolt is on a mission to build the world's greenest battery, leading Europe into a new era of sustainable energy. Our Data & AI team is building the next-gen connected factory, revolutionizing how batteries are manufactured and improving the quality and performance of our products. With Northvolt Ett, our first Gigafactory in Europe, we're setting a global example of advanced manufacturing powered by the cloud.

The Role:
We are seeking a talented Senior/Staff Data Engineer to join our Data & AI Team. In this role, you will design, build, and maintain the systems and infrastructure needed for data acquisition, storage, and analysis. Your primary focus will be to develop and optimize data pipelines, integrate diverse data sources, and ensure reliable data processing workflows. You'll be pivotal in building the data platform that powers product traceability, manufacturing monitoring, computer vision defect detection, and machine learning models for quality and performance prediction.

Key responsibilities include but are not limited to:

• Design, develop, and maintain scalable data pipelines and ETL processes for structured and unstructured data.
• Collaborate with cross-functional teams to understand data requirements and implement solutions that meet business needs.
• Optimize data workflows for performance, reliability, and efficiency, ensuring accurate data delivery to downstream applications.
• Implement data quality checks, monitoring, and logging to ensure the integrity and reliability of data pipelines.
• Evaluate and recommend new technologies, tools, and frameworks to improve data processing capabilities and infrastructure scalability.
• Work closely with data architects to design and implement data models and schema designs for business analytics and reporting needs.
• Support data scientists and analysts by providing clean and curated datasets for analysis and modeling.
• Troubleshoot and resolve data-related issues, including performance bottlenecks, data discrepancies, and system failures.
• Stay updated with industry trends and emerging technologies in data engineering.
• Leverage AWS/Azure cloud computing to design and process large datasets.