Data Science Engineer (d/f/m)
Henkel
Düsseldorf, DE
vor 4 Tg.

YOUR ROLE

  • Generate value from data by increasing, integrating, enriching, and distributing Henkel’s data-asset
  • Design, develop, and operate scalable and robust data pipelines using state-of-the-art data engineering practices. Advice and consult business to use data efficiently
  • Develop and operate scalable, agile, quality-first data platforms (DataOps) and enable sustainable data science deployment solutions (MLOps)
  • Be part of a team of data professionals in the Data & Analytics department. Advance the team with your expertise and extend and deepen your knowledge by strong collaboration within the team
  • Actively participate in cross-functional teams using agile methods to deliver high quality data products at a fast pace
  • Establish yourself as a reliable, creative, and positive partner across business to enable and identify data potential
  • YOUR SKILLS

  • Master’s degree in a computer science or other STEM field; PhD is a plus
  • Minimum 5 years of relevant experience in a data engineering environment
  • Extensive hands-on experience in cloud data ecosystems; covering data ingestion, data modeling, and data provisioning to consumers and downstream systems
  • Excellent coding skills in relevant languages (e.g. SQL, Python, C#, Scala). Experience in ETL / ELT design, data and interface specifications, quality assurance and testing methods.
  • Deep knowledge of data pipeline orchestration (e.g. ADF) and distributed computation frameworks (e.g. Azure Synapse, Spark)

  • Experience in implementing DataOps and MLOps concepts
  • Proven track record of delivering value from data. Experience in building robust, scalable, high-quality data products in iterations and integrating them into existing and new data-pipelines
  • Experience with agile methodologies in a professional development environment (CI / CD)
  • Fluent in English; German language skill is a plus
  • Henkel is an equal opportunity employer. We evaluate qualified applicants without regard to gender, origin, culture, mindset, generation, disability, religion and sexual orientation.

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