Senior Data Engineer ‏ (d/f/m) - part-time possible

at  henkel

At Henkel, you can build on a strong legacy and leading positions in both industrial and consumer businesses to reimagine and improve life every day. If you love challenging the status quo, join our community of 50,000 pioneers around the globe. The teams in our corporate functions enable the best in our dynamic businesses and in our people to maximize our company’s potential. With our leading brands, our cutting-edge technologies and our disruptive solutions, you will have countless opportunities to explore new paths and develop your skills. Grow within our future-led businesses, our diverse and vibrant culture and find a place where you simply belong. All to leave your mark for more sustainable growth.

YOUR SKILLS

• Bachelor’s degree in a computer science or other STEM field
• Minimum 5 years of relevant experience with data engineering in an Azure and/or Databricks environment
• Minimum 5 years of experience with SQL and Python development
• Background in agile development practices and in-depth experience with CI/CD and DataOps
• Proven track record in building robust, scalable, high-quality data products
• Fluent in English
  Full-time occupation is preferred but part-time would be possible (at least 80%).
  At Henkel, we come from a broad range of backgrounds, perspectives, and life experiences. We believe the uniqueness of all our employees is the power in us. Become part of the team and bring your uniqueness to us! We welcome all applications across different genders, origins, cultures, religions, sexual orientations, disabilities, and generations.

• You will be part of the Data Engineering Enablement team, one of the six teams that make up the Henkel Data Platform organization. As a senior data engineer, you will:
• Build the backend services, tooling and frameworks used by all data engineers across Henkel dX.
• Design, develop and operate scalable and robust data pipelines and source system integrations
• Advance the team with your expertise in state-of-the-art data engineering practices
• Collaborate with other data platform teams to deliver a user-centric, self-service distributed data and AI platform