Makersite is an award-winning data software company that empowers teams to manage product sustainability, cost, and compliance; simultaneously, from a web browser. Our mission is to help manufacturing companies make better decisions and create safer, more sustainable products through data-driven analysis. We believe that technology can help corporations to have a more positive impact on their environment. That is why we developed a platform that uses cutting edge technology, big data, and breakthrough algorithms to deliver product intelligence unlike anything on the market.
For manufacturing companies with complex supply chains that want to accelerate product development, build resilience or reduce costs, Makersite is a disruptive digital twin platform that uses AI to connect and enrich cross-departmental data into live models for analysis, collaboration and decision support. Digital twins can be used to understand how externalities like regulations, supply shortages etc. affect a business and help teams evaluate scenarios taking into account multiple criteria like costs, environment, compliance etc. at the same time.
Who We Are Looking For:
As a Data Engineer within our Services Team, you will play a crucial role in integrating new and existing data, managing the world´s largest supply chain database, and continuously seeking new sources of data to enhance our database´s capabilities. Your responsibilities will span from building data pipelines from internal and external sources and systems to understanding complex business problems and connecting them with technical data-driven solutions.
Locations: Berlin, Stuttgart, Munich or remote (EU)
Full-time
Integrate new and existing data into our hyper-connected databases
Manage and optimize the world's largest supply chain database.
Continuously seek and evaluate new sources of data that can be leveraged to enhance our database and provide customers with optimal feature development.
Build robust and scalable data pipelines from both internal and external sources.
Develop and maintain complex data models to support various business needs.
Collaborate with cross-functional teams to understand domain-specific challenges and translate these into technical requirements.
Implement data quality and validation processes to ensure the accuracy and reliability of data.
Stay updated with the latest advancements in data engineering technologies and methodologies.
Ensure adherence to confidentiality and data security standards.
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