Data Engineer (m/f/x)
Data Engineer (m/f/x)
EU (Remote)
Who You’ll Work For:
At Makersite, we're pioneering the future of sustainable product development and digital collaboration. As a leading platform for product lifecycle management (PLM), we empower companies to make smarter, more sustainable decisions across their entire supply chain. Our cutting-edge software enables teams to design, prototype, and manufacture with transparency, efficiency, and responsibility—reducing environmental impact while optimizing performance.
We're a fast-growing, innovative company that thrives on creativity, collaboration, and continuous learning. If you're passionate about technology, sustainability, and creating meaningful impact, we’d love to hear from you. Join us and be a part of shaping the future of manufacturing and product innovation.
Who we're looking for:
As part of our growing team, you will play a key role in shaping the future of sustainable product development. We’re looking for innovative, driven Data Engineers who are passionate about technology and sustainability to join us in building tools that enable companies to make smarter, more responsible decisions. In this role, you’ll have the opportunity to collaborate with talented professionals, contribute to cutting-edge projects, and help drive the digital transformation of industries worldwide. If you're ready to make an impact and contribute to meaningful change, we want to hear from you!
This role is a fixed, permanent position. All successful applicants will receive a permanent employment contract regardless of location.
The role:
Design, build, and maintain scalable data pipelines and infrastructure to support analytics and machine learning workflows.
Develop and optimize data storage solutions (e.g., data lakes, warehouses, databases) for performance, reliability, and scalability.
Ensure data quality, consistency, and accessibility through robust validation, cleaning, and transformation processes.
Collaborate with data scientists, analysts, and other stakeholders to understand data needs and translate them into technical solutions.
Integrate data from multiple internal and external sources, ensuring security and compliance with data governance policies.
Support machine learning initiatives by preparing, structuring, and serving data for model training, testing, and deployment.
Monitor, troubleshoot, and improve data systems for performance, cost-efficiency, and reliability.
Document processes, data flows, and best practices to ensure maintainability and knowledge sharing across the team.
Stay up to date with emerging data engineering tools, technologies, and best practices to continuously improve our data infrastructure.
