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Data Engineer Leader

vor 1 Woche


Basel, Basel-Stadt, Schweiz Lonza Biologics Porriño SLU Vollzeit
About Lonza

Lonza is a global leader in life sciences operating across five continents. We work in science, not relying on magic formulas to achieve our goals. Our greatest scientific solution lies in talented individuals working together, devising ideas that benefit businesses and people alike.

We let our people own their careers, empowering them to make genuine contributions that improve the world.

The Role: Lead Data Engineer at Lonza AG

This position offers an outstanding opportunity to lead innovative data initiatives in our R&D department located in Basel, Switzerland. As a Lead Data Engineer, you will craft the future of our bioinformatics projects by collaborating with colleagues, customers, and team members. You will define the scientific scope of projects and ensure seamless execution from start to finish.

As a key player, you will present your analytical results to project management and leadership teams, acting as a subject matter expert. Additionally, you will mentor junior team members, fostering a collaborative and inclusive environment that values exceptional contributions.

Key Responsibilities:
  1. Ensure timely and flawless delivery of data aspects in R&D projects, maintaining world-class quality and scientific rigor.
  2. Design and implement data pipelines and processing workflows in collaboration with peers from various R&D research groups.
  3. Share projects and findings with collaborators and present at external conferences, showcasing our innovative work.
  4. Prepare high-quality technical reports for both internal and external use, upholding proven standards of excellence.
  5. Define and successfully implement DataOps projects independently.
  6. Introduce and manage new bioinformatics tools and software, optimizing our data capabilities.
Requirements:
  1. Bachelor's degree in Bioinformatics, Computational Biology, Data Science, Computer Science, or a related quantitative field, or equivalent experience.
  2. Proven experience in building and maintaining DataOps pipelines in a cloud environment.
  3. Demonstrated ability to manage and complete complex projects across multiple teams with diverse technical backgrounds.
  4. Strong background in data governance and standardization practices.
  5. Proficiency in common scripting languages, showcasing technical prowess.