About the Role
At BASF | Nunhems, you will play a key role in helping R&D teams turn complex scientific data into valuable insights that support the development of healthier, more sustainable vegetable varieties. You will bridge the gap between scientists, business stakeholders, and technical teams, ensuring data is accessible, reliable, and ready to accelerate research and innovation.
Main Responsibilities
- Enable scientists and analysts to seamlessly access and work with data from genomics, phenotyping, field trials, laboratory systems, and analytics platforms through an integrated and governed data environment.
- Design, develop, and continuously improve the scientific data integration and virtualization platform, ensuring solutions create real value for the business.
- Drive the implementation and optimization of modern data solutions, with Databricks as a key technology within the ecosystem.
- Develop scalable and sustainable data architectures and solutions that support both current and future research needs.
- Collaborate closely with scientists, architects, security specialists, IT and platform partners to translate business requirements into effective technical solutions.
- Establish technical standards and support design reviews to ensure quality, consistency, and best practices across the Scientific Data Integration team.
Required Skills & Experience
- Master's degree in Data Science, Computer Science, or a related field.
- At least 5 years of experience in data engineering, ideally within an R&D or scientific environment.
- Hands-on experience (approximately 2 years) with Databricks.
- Strong knowledge of data integration, data pipelines, and cloud-based architectures.
- Experience with Python, preferably including PySpark for large-scale data processing.
- Knowledge of Azure and/or AWS cloud environments.
- Familiarity with source control and CI/CD practices using tools such as Git, Azure DevOps, or GitHub Actions.
- Excellent communication skills and professional proficiency in English.
About the Team
You will become part of a global and highly collaborative digital and R&D environment where science, technology, and innovation come together. The team values knowledge sharing, pragmatic problem solving, continuous learning, and delivering solutions that make a tangible difference for scientists and business users worldwide.
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