Data Engineer and Business Analyst for Supply Chain Innovation

hace 2 semanas

Madrid, Madrid, España Basf A tiempo completo
About Us

BASF Digital Hub Madrid is a hub for innovation and digital transformation, where we develop cutting-edge solutions to drive business growth and efficiency. Our team is passionate about creativity, experimentation, and collaboration, and we believe that the right approach is through trial and error and great people working together.

Our Team

The "Artificial Intelligence (AI) Solutions for Supply Chains" team is responsible for developing innovative solutions to derive insights from data that support better and faster business decisions. We implement AI-driven solutions in their complete lifecycle for users in supply chain management around the world.

Responsibilities

We are looking for a talented Data Engineer and Business Analyst to join our team and contribute to the development of our GenAI-oriented Supply Chain Intelligence platform. The successful candidate will be responsible for:

  • Working closely with project team members and stakeholders to understand business requirements and consult on activities
  • Translating business requirements into technical concepts, particularly regarding data engineering, data products, and data architecture frameworks
  • Driving the sustainable implementation of our GenAI-oriented Supply Chain Intelligence platform, including data integration, enterprise data product concepts, data science aspects, and GenAI functionalities
  • Creating product requirement documents and maintaining them in an agile working mode
  • Working in an international and agile DevOps environment and applying agile principles for setting priorities and managing multiple stakeholders
  • Sharing knowledge and expertise with colleagues and promoting a culture of AI-driven innovation within the organization
  • Managing communication with external vendors to validate the landscape design and integration concept
Qualifications

We are looking for a highly skilled and experienced professional with:

  • Bachelor or master's degree in information technology, software engineering, Computer Science, Data Science, or other data-centric disciplines
  • At least 4 years of professional implementation experience in data engineering/data science
  • Technical and professional knowledge, including:
    • Microsoft Azure cloud components for ML and Data Science
    • Developing data pipelines
    • Experience working with large data sets, relational databases, data integration, and related technologies
    • Expert knowledge of Python with focus on machine learning and data science related libraries

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