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Sr Specialist Scientific Data Engineering
Sr Specialist Scientific Data EngineeringNespresso Deutschland GmbH • Lausanne, ch
Sr Specialist Scientific Data Engineering

Sr Specialist Scientific Data Engineering

Nespresso Deutschland GmbH • Lausanne, ch
Il y a plus de 30 jours
Description de poste

Sr Specialist Scientific Data Engineering

Strategic Research Operations

Welcome to Nestlé Research, a global organization, with most of our passionate team located in Lausanne, Switzerland! Our work is powered by five specialized Nestlé Institutes and key strategic units. Here, we embrace fresh thinking and collaborate to create amazing solutions. How about taking a step inside our organization and discover the exciting research activities and expertise that drive us forward? Want to learn more!

At Nestlé Research, we place people at the core of everything we do, driven by a passion for innovation that inspires us to embrace change. Our commitment to staying at the forefront of science allows us to make a meaningful impact on our world, fostering a culture of creativity and growth. Join us in our mission to inspire people and ignite innovation as we work together to shape a better future.

Position Snapshot: Your opportunity to #breakthrough with us!

What we offer at Nestlé

Exciting opportunities to develop your career your way

Flexible working arrangements - facilitating creativity and collaboration.

A culture of respect, with diversity, equity and inclusion at its core.

A dynamic international environment empowering you to learn, develop and grow.

Don’t hesitate to connect with us during the recruitment process to learn more

Position Summary

Within our Computational Sciences department, as a Senior Specialist Scientific Data Engineering you will be responsible for delivering advanced data engineering capabilities to support Nestlé Research projects. Your main objective will be to design, build, and optimize robust data pipelines and architectures that enable efficient data access, integration, and analysis across diverse scientific domains. You will play a key role in enabling data-driven research by ensuring high-quality, scalable, and secure data infrastructure.

A Day in the Life of a Senior Specialist Scientific Data Engineering

  • Design and implement end-to-end scientific data pipelines, e.g. for Bioinformatics or Clinical or Omics, including data ingestion, transformation, storage, and analytics layers, tailored to scientific research use cases.
  • Develop and deploy scalable data architectures on premise (Linux) or cloud platforms, ensuring performance, reliability, and compliance with data governance standards.
  • Onboard and drive external developers as well as team up with other internal data specialists (data architects, data scientists, AI engineers, software developers…) to accelerate delivery in priority projects.
  • Work in cross-functional project teams in a research environment to define project objectives and deliverables, evaluate the need and identify the right technical approaches to solve business need.
  • Partner with other teams to gather functional requirements, and improve data quality, metadata management, and data discoverability.

What Will Make You Successful

  • Bachelors or Master’s or PhD in Bioinformatics, or Computer Science combined with life sciences or a related field
  • Significant professional experience - 7+ years - in designing and implementing data pipelines and architectures, in a research or scientific context, ideally in food or pharma industry
  • Familiarity with software engineering practices and development frameworks (Scrum, Agile, DevOps).
  • You have the following expertise and technical skills:
    • Solid foundations in data modeling, ETL/ELT processes, and distributed data systems.
    • Proficiency in Python and SQL for data manipulation and pipeline development.
    • Experience with DevOps tool stacks (e.g., Git, CI/CD).
    • Experience with cloud platforms (e.g., Azure, AWS) and orchestration tools (e.g., Airflow, Azure Data Factory).
    • Experience of working with data lake and data warehouse technologies - Snowflake, Databricks
    • Experience working with Linux and container technologies such as Openshift or Docker or Podman.
    • Experience with Bioinformatics or Clinical or Omics data pipelines
    • Familiarity with Data analysis and Machine learning capabilities and awareness of agentic architecture frameworks
  • Experience collaborating with external teams and driving project streams through others to deliver results
  • Experience in mentoring and guiding junior internal resources and interns
  • Excellent problem-solving, communication skills, strong stakeholder management skills and strong knowledge sharing skills
  • Fluent spoken and written English

Exciting Opportunity Ahead! After submitting your application, you will receive an invitation to create a short video introduction, guided by a few specific questions. This is your chance to showcase your personality and passion.

We kindly ask that you submit your video within 7 days of your application to ensure we can assess your profile thoroughly. Please note that if this step is not completed within the specified time, we will assume you have chosen to withdraw your application.

Nestlé is committed to the accessibility of its recruitment process. If you require an adaptation during the recruitment process, please do let us know so we can support you effectively. All information will be treated confidentially.

At Nestlé, we want to help shape a better and healthier world, inspire people to live healthier lives and deliver impact at a scale and pace that makes a difference. We do this by fostering a diverse, friendly, supportive, and collaborative environment, that creates positive disruption, embraces innovation, and empowers people and teams to win. We aim to hire friendly, respectful, inspiring people who care about the people’s lives that we touch every single day.

Be a force for good. Join Nestlé and visit us on www.nestle.com.

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Sr Specialist Scientific Data Engineering • Lausanne, ch

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